Psychological methodology Books

Book SynopsisThe authors provide a non-technical approach to quantitative data analysis and a user-friendly introduction to SPSS Statistics Version 19 for Windows. Trade Review"Alan Bryman and Duncan Cramer take the reader on a journey through their first steps in using SPSS and data entry, through to how to decide which statistical technique is the most appropriate for their research and how to interpret each aspect of their analyses. This book is one of the most comprehensive and accessible books available on the market." - Professor Dominic Upton, Head of Psychology, University of Worcester, UK"Bryman and Cramer’s Quantitative Data Analysis has long been one of the best texts in the field. Crucially it explains why something is done, as well as how. Most importantly it does it without recourse to daunting formulae and calculations. It takes students from the beginnings of data analysis, assuming no knowledge of either statistics or SPSS and by the end of it a student can be an accomplished analyst." - Malcolm Williams, Director, Cardiff University. School of Social Sciences, UK"A helpful, user friendly introduction for quantitative data analysis using SPSS designed for students in both psychology and sociology fields." - Andrada Ivanescu, East Carolina University, US, in The American Statistician"Alan Bryman and Duncan Cramer take the reader on a journey through their first steps in using SPSS and data entry, through to how to decide which statistical technique is the most appropriate for their research and how to interpret each aspect of their analyses. This book is one of the most comprehensive and accessible books available on the market." - Professor Dominic Upton, Head of Psychology, University of Worcester, UK"Bryman and Cramer’s Quantitative Data Analysis has long been one of the best texts in the field. Crucially, it explains why something is done, as well as how. Most importantly, it does it without recourse to daunting formulae and calculations. It takes students from the beginnings of data analysis, assuming no knowledge of either statistics or SPSS, and by the end of it a student can be an accomplished analyst." - Malcolm Williams, Director, Cardiff University. School of Social Sciences, UKTable of ContentsPreface. 1. Data Analysis and the Research Process. 2. Analyzing Data with Computers: First Steps with SPSS 19, 18 and 17. 3. Analyzing Data with Computers: Further Steps with SPSS 19, 18 and 17. 4. Concepts and Their Measurement. 5. Summarizing Data. 6. Sampling and Statistical Significance. 7. Bivariate Analysis: Exploring Differences between Scores on Two Variables. 8. Bivariate Analysis: Exploring Relationships. 9. Multivariate Analysis: Exploring Differences among Three or More Variables. 10. Multivariate Analysis: Exploring Relationships among Three or More Variables. 11. Aggregating Variables: Exploratory Factor Analysis. Answers to Exercises. Glossary. Bibliography. Index.

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Book SynopsisGives clear guidance on how to set up and conduct small scale research that is based in clinical practice Assumes no prior knowledge of qualitative research and is aimed specifically at psychotherapists Recognises development of the evidence base for psychotherapy through qualitative research as a key objective for practitioners.Trade Review"This is a useful and informative introductory book. It sparked my interest in pursuing some of the suggested methods and topics of research within my own setting." (Gestalt Journal of Australia and New Zealand, June 2010) Table of ContentsAbout the Editors vii Contributing Authors ix Preface xi Part I Engaging Qualitative Research and the Relational-centred Approach 1 Introduction 1 1 Qualitative Relational-centred Research: A 'Voyage of Discovery' 3 2 Competing Qualitative Research Traditions 13 3 Embodied Co-creation: Theory and Values for Relational Research 29 4 Challenging 'Evidence-based Practice' 45 5 Quality in Qualitative Relational-centred Research 59 Part II Relational-centred Research: Being and Doing 69 Introduction 69 6 Setting Up Research 71 7 The Research Encounter: Co-creating your Data 87 8 Embracing Relational Research: Learning from Therapy 107 9 Engaging 'Process' 127 10 Analysis of Data Linda Finlay Anna Madill 145 11 Relational Ethics 159 12 Becoming a Relational Researcher 175 Part III Relational-centred Research in Action 183 Introduction 183 13 'My Heart was Killing Me': A Hermeneutic Phenomenological Study of the Lived Experience of Anger Virginia Eatough 185 14 A Therapist's Portrait of a Clinical Encounter with a Somatizer Maria Luca 197 15 Relating through Difference: A Critical Narrative Analysis Darren Langdridge 213 16 A Journey into Survival and Coping by Women Survivors of Childhood Sexual Abuse Susan L Morrow 227 References 241 Index 259

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Book SynopsisThis textbook offers an accessible and comprehensive introduction to statistics for all undergraduate psychology students, but particularly those in their second and third years who have already covered an initial introductory course. It covers all of the key areas in quantitative methods including sampling, significance tests, regression, and multivariate techniques and incorporates a range of exercises and problems at the end of each chapter for the student to follow.The free CD-ROM with tutorial modules complements and enhances the exercises in the text, offers scope for distance learning, and makes both the traditional and non-traditional approaches much more accessible.Key points of the book are: an emphasis on measurement, data summaries and graphs; a clear explanation of statistical inference using sampling distributions and confidence intervals, making significance tests much easier to understand; and help for students to understand and judge Table of ContentsUncertainty and Psychological Research Variables and Measurement Exploring, Describing, Displaying and Summarizing Research Design and Probability Sampling Distributions and Confidence Intervals Statistical Models and Significance Tests Predicting a Quantitative Variable from a Categorical Variable The t Test and Analysis of Variance Quantitative Predictors Regression and Correlation Predicting Categorical Variables Contingency Tables and Chi-Square More Than Two Variables A Peek at Multivariate Analysis Putting Statistics into Perspective

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Book SynopsisAdvancing work to effectively study, understand, and serve the fastest growing U.S. ethnic minority population, this volume explicitly emphasizes the racial and ethnic diversity within this heterogeneous cultural group. The focus is on the complex historical roots of contemporary Latino/as, their diversity in skin-color and physiognomy, racial identity, ethnic identity, gender differences, immigration patterns, and acculturation. The work highlights how the complexities inherent in the diverse Latino/a experience, as specified throughout the topics covered in this volume, become critical elements of culturally responsive and racially conscious mental health treatment approaches. By addressing the complexities, within-group differences, and racially heterogeneity characteristic of U.S. Latino/as, this volume makes a significant contribution to the literature related to mental health treatments and interventions.Trade Review"Superb! Cultural Foundations and Interventions in Latino/a Mental Health is a must read for anyone interested in Latina/os. Hector Adames and Nayeli Chavez-Dueñas weaved psychological theory, research, and practice into a healing arpillera. This invaluable book is a timely and essential contribution to the field."– Lillian Comas-Diaz, Executive Director & Clinical Professor, George Washington University School of Medicine and Transcultural Mental Health Institute, USA"This is one of the most engaging, thorough, and practical books on Latino/a Mental Health."– Martin La Roche, Associate Professor, Harvard Medical School, USA. "This book offers a major contribution to understanding and effectively working with Latino/a students, families and mental health clients. It presents an excellent history of the journey of Latinos/a in the United States and their ability to maintain hope, dignity and connection to the past and future. The authors offer a powerful discussion of the role of skin color in Latino/a ethnic and cultural identity."– Joseph L. White, Professor Emeritus of Psychology and Psychiatry, University of California, Irvine, USA. Table of ContentsForeword Patricia Arredondo Part I: Socio-Cultural Foundations 1. The Diverse Historical Roots of Today’s Latino/as: Learning from our Past to Move into the Future 2. Skin Color Differences within Latino/as: Historical & Contemporary Implications of Colorism 3. The History of Latino/a in the United States: Journeys of Hope, Struggle, & Resilience Part II: Understanding Within Group Latino/a Differences 4. Socio-historical Construction of Latina/o Gender Ideologies: Integrating Indigenous and Contemporary Perspectives into Treatment 5. Adapting to a New Country: Models & Theories of Acculturation Applied to the Diverse Latino/a Population 6. Skin Color Matters: Towards a New Framework that Considers Racial and Ethnic Identity Development Among Latino/as Part III: Culturally Responsive and Racially Conscious Clinical Practice with Latino/as 7. Towards a Complex Understanding of Mental Health Service Utilization among Latino/as: Considering Context, Power, and Within Group Differences 8. Roots of Connectedness: Application of Latino/a Cultural Values in Mental Health Care 9. Culturally Responsive and Racially Conscious Mental Health Approaches with Latino/as Part IV: The Impact of Latino/a Psychology on Racially & Ethnically Diverse Students and Professionals 10. The Impact of Latino/a Psychology on Racially & Ethnically Diverse Students and Professionals

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Book SynopsisIn a time where new research methods are constantly being developed and science is evolving, researchers must continually educate themselves on cutting-edge methods and best practices related to their field. The second of three volumes, this Handbook provides comprehensive and up-to-date coverage of a variety of issues important in developing, designing, and collecting data to produce high-quality research efforts. First, leading scholars from around the world provide an in depth explanation of various advanced methodological techniques. In section two, chapters cover general important methodological considerations across all types of data collection. In the third section, the chapters cover self-report and behavioral measures and their considerations for use. In the fourth section, various psychological measures are covered. The final section of the handbook covers issues that directly concern qualitative data collection approaches. Throughout the book, examples and real-world research efforts from dozens of different disciplines are discussed.

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Book SynopsisInformation is very important for businesses. Businesses that use information correctly are successful while those that don't, decline. Social media is an important source of data. This data brings us to social media analytics. Surveys are no longer the only way to hear the voice of consumers. With the data obtained from social media platforms, businesses can devise marketing strategies. It provides a better understanding consumer behavior. As consumers are at the center of all business activities, it is unrealistic to succeed without understanding consumption patterns. Social media analytics is useful, especially for marketers. Marketers can evaluate the data to make strategic marketing plans. Social media analytics and consumer behavior are two important issues that need to be addressed together. The book differs in that it handles social media analytics from a different perspective. It is planned that social media analytics will be discussed in detail in terms of consumer

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Book SynopsisThe Handbook of Teaching Qualitative and Mixed Research Methods: A Step-by-Step Guide for Instructors presents diverse pedagogical approaches to teaching 71 qualitative and mixed methods.These tried-and-true methods are widely applicable to those teaching and those being trained in qualitative and mixed-methods research. The methods for data collection cover ethics, sampling, interviewing, recording observations of behavior, Indigenous and decolonizing methods and methodologies as well as visual and participatory methods. Methods for analyzing data include coding and finding themes, exploratory and inductive analysis, linguistic analysis, mixed-methods analysis, and comparative analysis. Each method has its own 1,500-word lesson (i.e., chapter) written by expert methodologists from around the globe. In these lessons, contributors give the reader a brief history of the method and describe how they teach it by including their best practicesâwith succinct, step-by-step instructionsâfocusing on student-centered experiential and active learning exercises.This comprehensive, one-of a-kind text is an essential reference for instructors who teach qualitative and/or mixed methods across the Social and Behavioral Sciences and other related disciplines, including Anthropology, Sociology, Education, and Health/Nursing research.Table of ContentsSection 1. Research Ethics 1. Teaching Ethics in Qualitative Research 2. Obtaining Consent: Why, What and How; Section 2. Sampling in Qualitative Research 3. Teaching Qualitative Sample Size Estimation 4. Non-probability Sampling 5. Collecting Data from Networked Populations: Snowball and Respondent-driven Sampling 6. Sampling Design for Qualitative Research: Teaching Theoretical Sampling for Cross-cultural Research; Section 3. Interviewing as Data Collection 7. Teaching Interviewing: How to Guide Conversations for Qualitative Research 8. Cognitive Interviewing for Questionnaire Design and Evaluation 9. Ethnographic Interviewing: The Life of Language among Families 10. Free-list Interviewing 11. Qualitative Interviewing in the Study of Culture 12. Personal Network Analysis 13. A Strategy to Practice Moderating in Focus Groups 14. Focus Group Interviewing Method; Section 4. Observations as Data Collection 15. Participant Observation: How to Be a Participant and Observer at the Same Time 16. Observation as Data Collection 17. How Behavior Observations Enrich Qualitative Researchers 18. Ethnography: A First Overarching Look 19. Rapid Ethnographic Assessment 20. Teaching Field Notes 21. Ethnographic Writing 22. Teaching Reflexivity and Positionality 23. Autoethnography: Sensitizing the "I"24. Social Media Data Analysis 25. Shooting Video for Social Science Research; Section 5. Indigenous and Decolonizing Methods 26. A Brief Introduction to Critical Indigenous Research Methodologies 27. Ethically Engaging Marginalized Communities in Research 28. Talanoa Research Methodology: Strategies for Teaching an Indigenous Methodology 29. Centering Indigenous Practice: Talking Circles as Participatory Action Research 30. Indigenous Data Sovereignty and Governance 31. A Black Feminist Life History Method: How to Center Black Women’s Voices 32. Sister–girl Talk: A Method for Group Interviewing Black Women 33. Community-engaged Partnership Research 34. Theater as Ethnographic Method; Section 6. Visual and Participatory Methods 35. Photovoice and Participatory Visual Elicitation Methods 36. Teaching Ethnographic Photovoice as a Method for Studying Marginalized Groups 37. Digital Storytelling as a Tool for Critical Narrative Research 38. Introduction to Interactive 3D e-Participatory Methods through the Lens of Urban Planning Projects 39. Art-based Methods for Qualitative Research with Younger Children 40. Reflecting on Place: Group Sketch Mapping; Section 7. Building Blocks and Basis of Analysis 41. Transcription: Understanding Its Analytical Power 42. Handling Multilingual Data: Transcription and Translation 43. Teaching Theme Identification 44. Finding Themes Using the Cutting and Sorting Approach: Guided Exercises with Interview Data 45. Creating Visual Variables: A First Step in Systematic Analysis of Videotaped Data 46. Developing a Codebook for a Case Participant 47. Coding in Action: Applying Codes at Various Levels 48. Teaching Intercoder Reliability Assessment 49. Teaching Qualitative Content Analysis 50. Context Matters: Conducting Word-based Analysis in Qualitative Research; Section 8. Grounded Theory, Phenomenology and Narrative Analysis 51. Doing Grounded Theory: Key Steps for Design, Data Collection, and Analysis 52. Phenomenological Interpretation: A Creative Lesson on Lived Experience 53. Narrative Analysis 54. Narrative Analysis: The Narrated, Non-narrated, and the Disnarrated 55. Teaching Meaning and Idioms in Life History Narratives; Section 9. Linguistic Analysis 56. Corpus Linguistics and Its Role in Qualitative Research 57. Teaching about Variation 58. Analyzing Language as Actions-in-interaction 59. Teaching Indexicality through a Focus on Identity 60. Teaching Discourse Analysis Using Political Texts 61. Using Critical Discourse Analysis to Understand Texts in Context; Section 10. Network Analysis and Cultural Domain Analysis 62. Mixed Semantic Network Analysis to Explore Discoursive and Cultural Landscapes 63. Walking in Your Footsteps: Using Qualitative Methods in Whole Network Analysis 64. Mapping the Structure of a Cultural Domain: Cultural Domain Analysis 65. Measuring Cultural Consonance; Section 11. Modeling and Comparative Analysis 66. Topic Models: Modeling from Text Corpora 67. Agent-based Modeling in Mixed Methods Research 68. Teaching Meta-themes: A Mixed Methods Approach 69. Teaching Comparative Ethnography: Two Examples from the Environmental Governance Field 70. Uncovering Causal Complexity with Qualitative Comparative Analysis 71. Concepts before Numbers: Teaching Effective Calibration Practices for Qualitative Comparative Analysis

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Book SynopsisUndertaking Capstone and Final Year Projects in Psychology serves a seminal purpose in guiding its readers to create a capstone project. The text employs traditional and emerging methodologies and methods in order to posit an exhaustive approach that the psychology students can adopt to see their project to fruition.The text aims at fortifying the reader's skills through the structure of its chapters as they begin to work on their capstone or final year project. The chapters collectively explore the varied aspects that are involved in the completion of a final year project, that is, beginning from the inception of the idea to laying the foundation, designing the project, analysing the data, and, finally, presenting the findings. The text guides the reader through each step and provides further guidance on approaching the idea, coming up with the research question, positioning it within the epistemological and ontological context, and constructing the theoreticTable of Contents1. The foundation. 2. Developing Skills. 3. Getting ready, set, go. 4. The interest. 5. Positioning. 6. Methodology spectrum. 7. Methods. 8. The analysis (empirical only). 9. Presentation. 10. Making impact with your research.

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Book SynopsisLongitudinal Structural Equation Modeling is a comprehensive resource that reviews structural equation modeling (SEM) strategies for longitudinal data to help readers determine which modeling options are available for which hypotheses. This accessibly written book explores a range of models, from basic to sophisticated, including the statistical and conceptual underpinnings that are the building blocks of the analyses. By exploring connections between models, it demonstrates how SEM is related to other longitudinal data techniques and shows when to choose one analysis over another. Newsom emphasizes concepts and practical guidance for applied research rather than focusing on mathematical proofs, and new terms are highlighted and defined in the glossary. Figures are included for every model along with detailed discussions of model specification and implementation issues and each chapter also includes examples of each model type, descriptions of model extensions, commeTrade Review"This is a "must have" volume on examining change from a SEM perspective. It is thoughtfully put together beginning with a number of basic principles/concepts in the latent variable approach to change (e.g., longitudinal measurement invariance, linear and nonlinear growth). It then moves into a number of intermediate approaches (cross-lagged panel models, latent class, latent transition, and latent growth mixture models). The final chapters provide more advanced topics (time series and dynamic structural equation models, survival analysis, and missing data). The various topics covered are extensive, clearly presented, and well supported with examples and references that readers can use to work through the analyses."Ronald H. Heck, University of Hawaii"This book offers a schematic, comprehensive, and well-structured resource for understanding, applying, and teaching most of the techniques related to Longitudinal SEM. The book follows a specific flow based on the difficulties of the topics. It starts with a clear introduction to latent variable modeling, then moves on widely used longitudinal applications (e.g., measurement invariance, cross-lagged panel models), and finally offers chapters on more advanced and recent topics (e.g., LST, Mixture Modeling, and DSEM). The structure of the book also allows the reader to directly access the topics of interest. Both from an applied and teaching perspective, it is difficult to think of a more complete and better structured book on longitudinal SEM."Enrico Perinelli, University of Trento (Italy)"I've cited Jason Newsom's first edition of Longitudinal Structural Equation Modeling many times, and his second edition continues the tradition of clear, accessible presentations that cover both the basics of analysis and modeling strategies for longitudinal data and extra details that experts would appreciate. An impressive, authoritative work."Rex Kline, Concordia UniversityTable of ContentsContentsList of FiguresList of TablesPreface to the Second EditonPreface to the First EditionAcknowledgementsExample Data SetsChapter 1. Review of Some Key Latent Variable PrinciplesChapter 2. Longitudinal Measurement InvarianceChapter 3. Structural Models for Comparing Dependent Means and Proportions Chapter 4. Fundamental Concepts of Stability and Change Chapter 5. Cross-Lagged Panel ModelsChapter 6. Latent State-Trait ModelsChapter 7. Linear Latent Growth Curve Models Chapter 8. Nonlinear Latent Growth Curve ModelsChapter 9. Nonlinear Latent Growth Curve ModelsChapter 10. Latent Class and Latent TransitionChapter 11. Growth Mixture Models Chapter 12. Intensive Longitudinal Models: Time Series and Dynamic Structural Equation Models Chapter 13. Survival Analysis Models Chapter 14. Missing Data and Attrition Appendix A: Notation Appendix B: Why Does the Single Occasion Scaling Constraint Approach Work? Appendix C: A Primer on the Calculus of ChangeGlossaryIndex

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Book SynopsisThis comprehensive book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language. Featuring a series of fully worked analyses of repeated measures data, the focus is placed on active learning through the analyses of the progressively more complicated models presented throughout the book. In this book, the authors offer an introduction to statistics entirely focused on repeated measures data beginning with very simple two-group comparisons and ending with multinomial regression models with many random effects'. Across 13 well-structured chapters, readers are provided with all the code necessary to run all the analyses and make all the plots in the book, as well as useful examples of how to interpret and write up their own analyses. This book provides an accessible introduction for readers in any field, with any level of statistical background. Senior undergraduate students, graduate students, and experienced researchers looking Table of ContentsPrefaceAcknowledgments1. Introduction: Experiments and Variables2. Probabilities, Likelihood, and Inference3. Fitting Bayesian Regression Models with brms4. Inspecting a ‘Single Group’ of Observations using a Bayesian Multilevel Model5. Comparing Two Groups of Observations: Factors and Contrasts6. Variation in Parameters (‘Random Effects’) and Model Comparison7. Comparing Many Groups, Interactions, and Posterior Predictive Checks8. Varying Variances, More about Priors, and Prior Predictive Checks9. Quantitative Predictors and their Interactions with Factors10. Logistic Regression and Signal Detection Theory Models11. Multiple Quantitative Predictors, Dealing with Large Models, and Bayesian ANOVA12. Multinomial and Ordinal Regression13. Writing up Experiments: An investigation of the Perception of Apparent Speaker Characteristics from Speech Acoustics

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Book SynopsisModels for Non-Modelers focuses not on how to design models but on how to understand and critically appraise them. Data and statistical models are widely used in disciplines such as epidemiology, climate science and systems design, but it can be difficult for those without the necessary training to understand and implement them.This book is for non-modelers, especially social scientists. Through extensive examination of some common models both in visual and text form, this book shows these non-modellers how to understand the problems, both in the logic and implementation of such models. It includes in-depth worked examples and boxed text for more technical aspects. It does not require the reader to have in-depth mathematical knowledge. Also working through some common models in epidemiology and climate change scholarship, it examines AI and the problem of causality.This book will be suitable for graduate students and researchers in the social sciences who woulTrade Review"Models for Non-Modelers is a very timely and up-to-date comment on a central theme of scientific work, the use of models. It helps the interested reader to better understand important challenges of knowledge production in an era of critical debate regarding the concept of truth. Furthermore, to understand the research community’s strengths and limitations to produce new knowledge, which can be useful for handling complex environmental, economic and societal challenges like climate change and pandemics. It is highly recommended for a broad audience spanning from the interested public to students and researchers in development studies, environmental sciences, public health, and many other fields of science." -- Per-Olof Östergren, Professor in Social Medicine, Lund University, Sweden"This is a mind-opening critical, and pedagogical, scrutiny of scientific reasoning about the fateful issues of our time, from "Limits to Growth" to climate change and artificial intelligence." --Göran Therborn, Professor Emeritus of Sociology, University of Cambridge, UK"Models walk a fine balance between simplicity and complexity to make it possible for us to summarize, make sense of, and sometimes predict a complicated world. How to illuminate the importance of models for scientists’ work and its communication to the public? Göran Djurfeldt’s answer is to ’teach by illustration.’ Occam’s razor of parsimony guides the author both in his style of presentation and in his approach to models themselves. This book is enlivened by both subject-specific and mathematical nuance at key intersections." -- Christopher Swader, Associate Professor of Sociology, Lund University, SwedenTable of Contents1. Limits to Growth: A Mother of all Models? 2. Epidemiological Models 3. Weather and Climate Models 4. Artificial Intelligence 5. Spatial Data and Models 6. Tragedy of the Commons 7. Conclusions: Whereto from Here?

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Book SynopsisBurnout: A Guide to Identifying Burnout and Pathways to Recovery is the first complete self-help guide to burnout, based on groundbreaking new research. Burnout is widespread among high achievers in the workplace, and the problem is becoming more prevalent and profound in its impact. This book contains new evidence-based tools for readers to work out for themselves whether they have burnout and generate a plan for recovery based on their personal situation. Chapters show readers how to recognise their own burnout patterns and how far they may have travelled into burnout territory, and provide research-based management approaches to help them regain their passions and build their resilience. Offering fascinating new insights into the biology of burnout, and stories from people who have rebounded from it, the book acts as a complete guide for anyone who suspects they may have burnout, for their friends and families, and for health professionals and employerTrade Review'I cried reading parts of this book. Profoundly insightful, with information that is superbly liberating about a phenomenon that imprisons too many of us. Highly recommend.' Dr. Sonia Henry, bestselling author of Going Under 'No one wants to cause burnout in others or be the victim of burnout. Avoiding both calamities requires a much deeper and clearer understanding of what causes burnout and what cures it. This book does precisely that.' Adrian Piccoli, Professor, Gonski Institute for Education'A must for every senior executive and all HR professionals.' Warren Hogan, banker and economist'Lawyers need to read this book: burnout doesn’t have to mean the end of your career.' Alice Cooney, Principal Solicitor, Office of Public Prosecutions VictoriaTable of ContentsPART 1 What is burnout? 1. Burnout: Forerunners and variants 2. Burnout: Its modern history 3. Defining and identifying burnout 4. The Sydney studies 5. What burnout is NOT 6. Burnout versus depression 7. The biology of burnout PART 2 Causes of burnout: The seed and the soil 8. The workers’ dilemma 9. The toxic workplace 10. Occupations at high risk 11. Forgotten caregivers 12. Predisposing factors 13. Perfectionism PART 3 Overcoming burnout and rekindling the flame 14. Resolving burnout: An introduction 15. For managers 16. For workers and caregivers 17. De-stressing 18. Managing perfectionism 19. Pulling it all together 20. A final note and a personal story of Grace under pressure PART 4 Appendices Appendix A: The Sydney Burnout Measure (SBM) Appendix B: Workplace triggers Appendix C: Perfectionism scale Appendix D: Resources for workers and caregivers

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Book SynopsisMultivariate Statistical Methods: A Primer offers an introduction to multivariate statistical methods in a rigorous yet intuitive way, without an excess of mathematical details. In this fifth edition, all chapters have been revised and updated, with clearer and more direct language than in previous editions, and with more up-to-date examples, exercises, and references, in areas as diverse as biology, environmental sciences, economics, social medicine, and politics.Featuresâ A concise and accessible conceptual approach that requires minimal mathematical background.â Suitable for a wide range of applied statisticians and professionals from the natural and social sciences.â Presents all the key topics for a multivariate statistics course.â The R code in the appendices has been updated, and there is a new appendix introducing programming basics for R.â The data from examples and exercises are available on a companion website.This book con

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Book SynopsisThis innovative book proposes an entirely new approach to social research, presenting practical ways to discover people's life contexts in order to understand why they do what they do, which is essential for any forms of research that need to understand people.Taking a novel approach that goes beyond traditional categorisations of qualitative and quantitative research, the book starts by discussing the real basis of all research methods in social relationships, before detailing the methods for finding out about a person's life contexts in very practical terms, accompanied by suggested questions, advice, and research tricks to help you progress. The various life contexts are then worked through chapter by chapter. Drawing on the rich and varied research experiences of all the authors, examples are given throughout, with later chapters focusing on specific research areas.Conducting Contextual Research is essential reading for postgraduate students an

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Book SynopsisPreparing Literature Reviews is an accessible guide that provides easy to follow step-by-step advice on how to prepare qualitative and quantitative literature reviews. The 6th edition of this bestselling book retains its original lauded features of clear style and organization while bringing new chapters into the fold to address mixed-methods and theoretical frameworks in conducting reviews of literature.The text walks the reader through both the conceptualization and the writing stages, offering templates for fostering different phases of designing and drafting required to complete the process of conducting a review of literature from start to finish, in empirical articles, theses, or dissertations. New examples of literature reviews utilizing various approaches have been added, and there is also additional coverage of concepts such as literature organization, plagiarism, reviewing, topic selection, and writing. Commentary on literature in a variety of fields as

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Book SynopsisElections are random events.From individuals deciding whether to vote, to individuals deciding who to vote for, to election authorities deciding what to count, the outcomes of competitive democratic elections are rarely known until election day or beyond. Understanding Electionsexplores this random phenomenon from three primary points of view: predicting the election outcome using opinion polls, testing the election outcome using government-reported data, and exploring election data to better understand the people.Written for those with only a brief introduction to statistics, this book takes you on a statistical journey from how polls are taken to how they can and should be used to estimate current popular opinion. Once an understanding of the election process is built, we turn towards testing elections for evidence of unfairness. While holding elections has become the de facto proof of government legitimacy, those electoral process

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisOur world is complex. To make sense of it, data analysts routinely fit sophisticated statistical or machine learning models. Interpreting the results produced by such models can be challenging, and researchers often struggle to communicate their findings to colleagues and stakeholders. Model to Meaning is a book designed to bridge that gap. It is a practical guide for anyone who needs to translate model outputs into accurate insights that are accessible to a wide audience.Features: Presents a simple and powerful conceptual framework to interpret the results from a wide variety of statistical or machine learning models. Features in-depth case studies covering topics such as causal inference, experiments, interactions, categorical variables, multilevel regression, weighting, and machine learning. Includes extensive practical examples in both R and Python using the marginaleffects software. Accompanied by comprehensive online documentation, tutorials, and bonus case studies. Model to Meaning introduces a simple and powerful conceptual framework to help analysts describe the statistical quantities that can shed light on their research questions, estimate those quantities, and communicate the results clearly and rigorously. Based on this framework, the book proposes a consistent workflow that can be applied to (almost) any statistical or machine learning model. Readers will learn how to transform complex parameter estimates into quantities that are readily interpretable, intuitive, and understandable.Written for data scientists, researchers, and students, the book speaks to newcomers seeking practical skills, and to experienced analysts who are ready to adopt new tools and rethink entrenched habits. It offers useful ideas, concrete workflows, powerful software, and detailed case studies, presented using real-world data and code examples.

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Book SynopsisAn R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner's Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website. Table of ContentsPreface Acknowledgments About the Author CHAPTER 1 • Beyond Two Variables and Null Hypothesis Significance Testing Confidence Intervals Effect Size Meta-Analysis Chapter 1: Summary of Key Functions (AKA: Function Cheat Sheet) CHAPTER 2 • Advanced Data Screening, Outliers, and Missing Values Data Management Coding Missing Values Screening Data Chapter 2: Summary of Key Functions (AKA: Function Cheat Sheet) CHAPTER 3 • Statistical Control Including a Third Variable in Graphs Including a Third Variable Quantitatively Chapter 3: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 3: R Instructions to Accompany Warner (2020b) CHAPTER 4 • Statistical Control With Regression Analysis Visualizing Associations Between Three Variables Performing Regressions and Semipartial Correlations Chapter 4: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 4: R Instructions to Accompany Warner (2020b) CHAPTER 5 • Beyond Three Variables: Regression With Multiple Predictors Standard Regression User-Determined Regression Data-Driven Regression Chapter 5: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 5: R Instructions to Accompany Warner (2020b) CHAPTER 6 • Regression With Dummy Variables One-Way Between-Subjects Analysis of Variance (ANOVA) Regression With Dummy Variables Regression With Quantitative and Dummy Variables Chapter 6: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 6: R Instructions to Accompany Warner (2020b) CHAPTER 7 • Moderation Interactions With Categorical Predictors Interactions With a Categorical and Quantitative Predictor Interactions With Two Quantitative Predictors Interactions with a Categorical and Quantitative Predictor Interactions with Two Quantitative Predictors Chapter 7: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 7: R Instructions to Accompany Warner (2020b) CHAPTER 8 • Analysis of Covariance Checking Assumptions Performing ANCOVA Presenting Results Chapter 8: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 8: R Instructions to Accompany Warner (2020b) CHAPTER 9 • Mediation Checking Assumptions Performing Mediation Analysis Presenting Results Chapter 9: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 9: R Instructions to Accompany Warner (2020b) CHAPTER 10 • Discriminant Analysis Checking Assumptions Performing Discriminant Analysis Presenting Results Chapter 10: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 10: R Instructions to Accompany Warner (2020b) CHAPTER 11 • Multivariate Analysis of Variance Checking Assumptions Performing Multivariate Analysis of Variance Performing Factorial Multivariate Analysis of Variance Chapter 11: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 11: R Instructions to Accompany Warner (2020b) CHAPTER 12 • Exploratory Factor Analysis Performing Principal Components Analysis Performing Principal Axis Factor Analysis Chapter 12: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 12: R Instructions to Accompany Warner (2020b) CHAPTER 13 • Reliability and Validity for Multiple-Item Scales Test-Retest Reliability Factor Analysis Internal Reliability and Creating Scale Scores Chapter 13: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 13: R Instructions to Accompany Warner (2020b) CHAPTER 14 • Repeated-Measures Tests: Further Exploration Checking Assumptions One-Way Repeated-Measures Analysis of Variance Mixed Analysis of Variance Chapter 14: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 14: R Instructions to Accompany Warner (2020b) CHAPTER 15 • Brief Introduction to Latent-Variable Structural Equation Modeling Measurement Models Mediation With Latent-Variable Structural Equation Modeling Chapter 15: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 15: R Instructions to Accompany Warner (2020b) CHAPTER 16 • Binary Logistic Regression Getting Familiar With the Data Binary Logistic Regression Presenting Results Chapter 16: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 16: R Instructions to Accompany Warner (2020b) CHAPTER 17 • Additional Statistical Techniques Dealing With Time Dealing With Odd Distributions Dealing With Interdependence Concluding Thoughts References

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Book Synopsis

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Book SynopsisAn accessible and practical guide to the use of applied regression models in testing and evaluating hypotheses dealing with social relationships, with example applications using relevant statistical methods in both Stata and R.Trade Review'This textbook on applied regression by Poston, Conde, and Field is well suited for teaching graduate students in all of the social science fields, but is especially suited for demography, population studies, and public health. It is an excellent contribution to the teaching and practice of regression analysis in the twenty-first century that also can serve as a useful reference book for practitioners.' David Swanson, University of California, Riverside'This textbook successfully combines theoretical statistical concepts and empirical research examples of applied regression models, from the basic to advanced ones. The best part is the detailed interpretations of the results of statistical analyses. Readers can truly understand the meanings and usages of these statistical numbers.' Lang-Wen Huang, Soochow University, Taipei'Applied Regression Models in the Social Sciences excels in its focus on the application and interpretation of various regression models and its inclusion of commands in Stata and R. Its sequencing and topical coverage set it apart from others in that the reader is guided through the entire research process with a multitude of examples. This will be a valuable resource to faculty, students, and applied researchers alike.' Ginny Garcia-Alexander, University of Texas at San Antonio'This textbook fills a critical void in the market for statistical tutorials by bridging the gap between elementary and advanced statistics and providing real-world examples in both Stata and R, allowing students to develop proficiency in the statistical software environments in highest demand. It strikes the perfect balance, neither oversimplifying nor overwhelming with complex mathematics, making it the ideal companion for graduate students seeking a solid foundation in the skills needed to generate social science findings with advanced insights. From correlation analysis to multi-level modeling, this comprehensive and versatile book covers a wide range of regression techniques, equipping learners with a diverse toolkit for trustworthy data analysis and allowing them to transition from the classroom to the laboratory with confidence. The authors' expertise shines through in this clear, comprehensive, and engaging book that is destined to be an indispensable resource.' Stephanie Bohon, University of TennesseeTable of ContentsList of figures; List of tables; Preface; 1. Introduction; 2. Undertaking statistical analysis using Stata; 3. Undertaking statistical analysis using R; 4. Descriptive statistics and the normal distribution; 5. Statistical tables and cross-tabulations; 6. Bivariate regression and correlation and statistical inference; 7. Multiple regression and correlation; 8. Regression assumptions and diagnostics and robust regression; 9. Missing data; 10. Issues of survey design; 11. Binomial logistic regression; 12. Ordinal logistic regression; 13. Multinomial logistic regression; 14. Count regression; 15. Survival analysis; 16. Multilevel models; 17. Other issues and final; References; Index.

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Book SynopsisThe bestselling guide to reporting writing, updated and reworked for today's practice Essentials of Assessment Report Writing offers effective solutions to the creation of reader-friendly, yet targeted, psychological, and educational assessment reports.Table of ContentsSeries Preface ix Preface to the Second Edition xi Acknowledgements xiii One Introduction and Overview 1 Two Make Your Reports Classy and Gorgeous 11 Three Writing with Clarity, Style, and Purpose 30 Four Introductory Sections of the Report 73 Five Behavioral Observations 97 Six Communicating Test Results 128 Seven Diagnostic Impressions and Summary 157 Eight Personality Assessment (by Rita W. McCleary) 166 Nine Recommendations 197 Ten Special Issues in Report Writing 230 Eleven Tips for Writing Evaluation Reports (by John O. Willis) 249 Twelve Annotated Case Reports 260 References 445 Index 452

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Book SynopsisFeaturing a wealth of examples and practical advice, this is the best possible resource for students conducting research online. Bringing together key topics, this student-friendly textbook guides you through the design and execution of different online research methods.Trade Review"Neil Coulson captures the nuances of designing psychological research studies online in an accessible and thought-provoking way. An essential read for anyone wishing to embrace the Internet as a research tool." - Jenny Mercer, Principal Lecturer, School of Health Sciences, Cardiff Metropolitan University, UK "Throughout the book Neil Coulson shares good practice and, in so doing, models how to conduct research in the online milieu that is of a high ethical, methodological and scientific standard." - Karen Rodham, Professor of Health Psychology, Staffordshire University, UKTable of Contents1. Introduction to Online Research 2. Online Interviews 3. Online Focus Groups 4. Online Surveys 5. Online Experiments 6. Social Media as a Research Environment.

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Book SynopsisA unique and important resource, full of critical practical knowledge and technical details made readily accessible. - Tiffany Ito, University of Colorado at Boulder A comprehensive and engaging guide to EEG methods in social neuroscience; Dickter and Kiefabber offer practical details for conducting EEG research in a social/personality lab, with a broad perspective on how neuroscience can inform psychology. This is a unique and invaluable resource - a must-have for scientists interested in the social brain. - David M. Amodio, New York University Electroencephalography (EEG) has seen a dramatic increase in application as a research tool in the psychological sciences in recent years. This book provides an introduction to the technology and techniques of EEG in the context of social and cognitive neuroscience research that will appeal to investigators (students or researchers) wishTrade ReviewA unique and important resource, full of critical practical knowledge and technical details made readily accessible. -- Tiffany ItoA comprehensive and engaging guide to EEG methods in social neuroscience; Dickter and Kiefabber offer practical details for conducting EEG research in a social/personality lab, with a broad perspective on how neuroscience can inform psychology. This is a unique and invaluable resource—a must-have for scientists interested in the social brain. -- David M. AmodioTable of ContentsChapter 1 – Introduction to Social Neuroscience Chapter 2 – From Cortex to Computer: The Principles of Recording EEG Chapter 3 – The EEG Laboratory Chapter 4 – Getting Started with Data Analysis: Data Pre-Processing Chapter 5 – Time-Domain Analysis Chapter 6 – Frequency-Domain Analysis Chapter 7 – Time-Frequency Analysis Chapter 8 – Current Domains & Future Directions

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Book SynopsisThis unique text provides a comprehensive framework for creating, managing, and interpreting qualitative research studies that yield valid and useful information. Examples of studies from a wide range of disciplines illustrate the strengths, limitations, and applications of the primary qualitative methods: in-depth interviews, focus group discussions, ethnography, content analysis, and case study and narrative research. Following a consistent format, chapters show students and researchers how to implement each method within a paradigm-neutral and flexible Total Quality Framework (TQF) comprising four interrelated components: Credibility, Analyzability, Transparency, and Usefulness. Unlike other texts that relegate quality issues to one or two chapters, detailed discussions of such crucial topics as construct validity, interresearcher reliability, researcher bias, and verification strategies are featured throughout. The book also addresses applications of the TQF to the writing, reviTrade Review"The presentation of a TQF that can be used both to evaluate published studies and create high-quality studies is a unique contribution to the field of qualitative inquiry. The TQF will be particularly helpful to graduate students who are venturing into qualitative research. The authors skillfully guide the reader through the various modes of data collection and analysis. They provide detailed guidance on key methodological issues, such as decisions regarding sample size, conducting telephone versus face-to-face interviews, and uses of focus groups."--Margaret J. Bull, PhD, RN, Marquette University College of Nursing “A most original contribution that has been put together with the greatest of care. I applaud the authors for dividing each of the five methods chapters into well-organized sections that cover all aspects of the methods and explain how and why to apply TQF principles. Each chapter ends with an exceptionally effective case study to illustrate the concepts described. Other highlights of the book include the discussion topics and exercises to further readers’ thinking and understanding. This will be a great text for my senior-level honors seminar in qualitative research design."--Kimberley Ducey, PhD, Department of Sociology, University of Winnipeg, Canada “This is an excellent text for a graduate qualitative research course, as well as a valuable reference for professionals. Well-written and easy to use, it provides a practical approach for students by incorporating exercises, case studies, web resources, and discussion topics. The latest research trends are discussed throughout, such as email IDIs, mobile ethnography, and synchronous versus asynchronous online discussion boards. The authors’ years of experience in conducting qualitative research make this book not only informative, but interesting to read.”--Candice R. Hollenbeck, PhD, Department of Marketing, University of Georgia “A much-needed, pathbreaking book that will help set new standards of authoritativeness and excellence in qualitative research. The TQF is a powerful approach that can inform all types of research. I particularly like the authors' thorough attention to context, which they carefully explain in the introduction and develop throughout the book; this is one of the most important aspects of qualitative research."--Gerald Kosicki, PhD, School of Communication, The Ohio State University “The writing is clear with helpful illustrative examples. Strengths of the book include its user-friendly narrative language and the effective applied exercises and case studies at the end of each chapter.”--Mary I. Dereshiwsky, PhD, Department of Educational Leadership, Northern Arizona University -Roller and Lavrakas do a fantastic job of identifying strengths and limitations of each design model.--The Qualitative Report, 1/1/2018ƒƒThis book is suffused with the elements of what the authors call the total quality framework--namely credibility, analyzability, transparency, and usefulness. Each chapter is built around this framework so the important decisions needed throughout the stages of a qualitative research study are covered….Good use is made of chapter summaries and discussion topics and worked examples….Where appropriate, the advantages and disadvantages of preparing for, collecting, and analyzing data using technology is explored providing an additional dimension to the text. I would recommend this book to educators, researchers, and postgraduate students who are undertaking qualitative research.--Nurse Researcher, 1/1/2016ƒƒA hands-on, innovative, integrated methods text….The framework provides principles and practices for researchers to apply throughout the research process so that they are more likely to gather high-quality data, come to a more complete and valid interpretation of their data, and generate and present useful outcomes….The book contains chapters on each of the main qualitative methods: in-depth interviews, focus groups, ethnography, content analysis, and case studies. The authors, in keeping with the integrated approach of their model, in parallel fashion apply each of the four elements of the framework to each technique and its particular requirements. This feature alone is a major strength of this work. But each method chapter contains some additional valuable elements, such as skills researchers must bring to that particular technique, strengths and weaknesses of that approach, and ethical considerations. The authors also provide a case study at the end of each chapter that is an example of a research project utilizing the TQF standards for that specific method. If that weren't enough, the final chapter focuses on how to use the TQF to assess the quality of qualitative studies done by others--or at least, grant or project proposals….The book itself is very well organized and well written….Section headings and parallel organization make it easy to jump back and forth, and chapter summaries along with an extensive glossary likewise aid the reader….Overall, Roller and Lavrakas have done social science scholars of all stripes a big favor.--Public Opinion Quarterly, 5/1/2016ƒƒReaders will benefit from the book's organization, with its similarly formatted chapters, and from the frequent examples, bulleted lists, diagrams, and annotated bibliographies at the end of the chapters. The overall presentation facilitates comprehension of what can be, for some, difficult content….This is an outstanding adjunctive resource for those using particular research paradigms (e.g., grounded theory, phenomenology, ethnography, etc.) and for those in need of a framework to ensure rigor in any qualitative research study. The book provides a new, fresh, and meticulous approach to creating, understanding, using, and evaluating qualitative research. (review by Martha M. Scheckel, PhD, RN)--Doody's Review Service, 7/10/2015Table of Contents1. Making Sense of the Human Experience with Qualitative Research 1.1. Introduction 1.2. Unique Attributes Associated with Qualitative Research 1.3. The Total Quality Framework and the Reason for This Book 1.4. Overall Organization of the Book and Its Chapters 1.5. The Glossary 2. The Total Quality Framework Chapter Preview 2.1. Introduction 2.2. Paradigms and Frameworks 2.3. What Is the Total Quality Framework? 2.4. Applying the Total Quality Framework 2.5. Chapter Summary Suggested Further Reading 3. Interview Method: In-Depth Interviews Chapter Preview 3.1. Introduction 3.2. Four Modes of the In-Depth Interview Method 3.3. Applying the Total Quality Framework Approach to the In-Depth Interview Method 3.4. Chapter Summary 3.5. Exercises and Discussion Topics Suggested Further Reading Web Resource 4. Interview Method: Focus Group Discussions Chapter Preview 4.1. Introduction 4.2. Three Modes of the Group Discussion Method 4.3. Applying the Total Quality Framework Approach to the Group Discussion Method 4.4. Chapter Summary 4.5. Exercises and Discussion Topics Suggested Further Reading Web Resources 5. Observation Method: Ethnography Chapter Preview 5.1. Introduction 5.2. Ethnography in the Digital Age 5.3. Applying the Total Quality Framework Approach to Ethnography 5.4. Chapter Summary 5.5. Exercises and Discussion Topics Suggested Further Reading Web Resources 6. Qualitative Content Analysis Chapter Preview 6.1. Introduction 6.2. Computer-Assisted Qualitative Content Analysis 6.3. Applying the Total Quality Framework Approach to Qualitative Content Analysis 6.4. Chapter Summary 6.5. Exercises and Discussion Topics Web Resources 7. Multiple Methods in Case-Centered Approaches: Case Study and Narrative Research Chapter Preview 7.1. Introduction 7.2. Process in Case-Centered Research 7.3. The Total Quality Framework Approach to Case-Centered Research 7.4. Chapter Summary 7.5. Exercises and Discussion Topics Suggested Further Reading Web Resource 8. The Total Quality Framework Research Proposal and Other Practical Applications of the Total Quality Framework Chapter Preview 8.1. Introduction 8.2. Section-by-Section Discussion of the Total Quality Framework Research Proposal 8.3. Evaluating Proposals Using the Total Quality Framework 8.4. Related Uses of the Total Quality Framework in Reviewing Research Reports 8.5. Chapter Summary Glossary References Author Index Subject Index About the Authors

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Book SynopsisWidely regarded as a standard clinical resource, this book helps practitioners think outside the mental health box and recognize when a client may need a medical evaluation. Part I provides an accessible overview of symptoms that can be observed in a standard mental status examination and may point to medical illness. Engaging case vignettes and interviewing pointers help readers hone their diagnostic skills. Part II presents concise facts--including basic medical information and physical and mental symptoms--on more than 60 diseases and syndromes. An easy-to-read chart in Part III cross-tabulates all of the disorders and symptoms for quick reference and comparison. New to This Edition *Reflects more than 15 years of advances in medical and mental health knowledge. *Updated throughout for DSM-5. *Additional medical disorders: celiac disease, traumatic brain injury, heavy-metal toxicity, and others. *Updated links to further reading on each health condition.Trade Review"This factual, current, and well-written guide is necessary reading for all clinicians who desire to sharpen their diagnostic skills. Morrison addresses the problems presented by psychiatric patients who may suffer from medical disorders, helping the clinician make sense of symptom presentations that are often confusing and on occasion mysterious and baffling. With tables, lists, and detailed explanations, this book establishes order and method in the examination of the complex patient. This second edition carries on the quality of the first, but is greatly enhanced by more information, new insights and clinical revelations, and a pragmatic interpretation of the latest findings."--Rodrigo A. Muñoz, MD, Department of Psychiatry, University of California, San Diego; past president, American Psychiatric Association “The ability to differentiate medical and psychological sources of psychological symptoms is a core competency in case formulation and treatment planning. Morrison's succinct book helps clinicians with this critical task better than any other. The book is cross-indexed so information is rapidly available. It is replete with case examples and interesting historical references, and benefits from Morrison's wit and humor. An outstanding contribution.”--Tracy D. Eells, PhD, Department of Psychiatry and Behavioral Sciences, University of Louisville "The second edition of this authoritative work covers a topic that is far too often ignored in the training and practice of mental health practitioners. The book is comprehensive, well organized, and easy to read. Morrison’s engaging style and inclusion of numerous summary tables make the book particularly accessible. This is an essential resource that should be on every clinician’s bookshelf or e-reader."--Martin M. Antony, PhD, ABPP, Department of Psychology, Toronto Metropolitan University, Canada "I used the first edition for many years to train doctoral students in clinical psychology, and found it to greatly enhance their training. I have no doubt that the second edition also will be extremely popular among students. The text is compelling and easy to read. It helps students and busy professionals quickly explore alternative diagnoses to avoid misdiagnosing medical disorders as psychological illnesses."--Leslie A. Robinson, PhD, Director, Clinical Health Track; Director, Center for Health Promotion and Evaluation, Department of Psychology, University of Memphis "Although most therapists are not medical specialists, we do not treat disembodied persons. Morrison alerts us to the most common mental symptoms that might be due to physical disorders, and heightens our diagnostic acumen. His efficient presentation, using both narrative and tables, can alert us to problems we might not have asked about and make treatment more comprehensive and effective. This updated second edition--written in the intelligent, experienced, and modest voice we have come to expect from Morrison--is a foundational resource for all therapists."--Edward L. Zuckerman, PhD, author of Clinician's Thesaurus -James Morrison's book is a gem. He addresses common medical illnesses that produce psychological symptoms in a refreshing manner, making the book an excellent review text for fellow psychiatrists and nonphysician psychotherapists....His occasionally tongue-in-cheek style makes for pleasant readability without minimizing the importance of his message....Tables...are laid out in easily readable form and useful for quick cross-referencing....This is book worth its weight in gold: it is eminently readable and can save some lives and bring improvement to many others. (on the first edition)--Journal of the American Medical Association, 03/09/2015ƒƒAt once a primer on the collaboration of psychotherapist and physician and a useful reference book for this purpose. Although it is intended for psychotherapists with limited medical training, it may also be useful to primary care physicians and other medical clinicians who may be the first contact for patients who present with psychiatric symptoms. (on the first edition)--Psychiatric Services, 03/09/2015Table of ContentsIntroduction I. A Review of Symptoms The Need for Evaluation Observing the Mental Status Appearance and Behavior Mood (Affect) Speech Content of Thought Intellectual Resources Insight and Judgment Personality Change Diagnostic Principles II. 66 Disorders Adrenal Insufficiency AIDS Altitude Sickness Amyotrophic Lateral Sclerosis Antidiuretic Hormone, Inappropriate Secretion Brain Abscess Brain Tumor Cancer Carcinoid Syndrome Cardiac Arrhythmias Celiac Disease Cerebrovascular Accident (Stroke) Chronic Obstructive Lung Disease Congestive Heart Failure Cryptococcosis Cushing's Syndrome Diabetes Mellitus Epilepsy Fibromyalgia Heavy-Metal Toxicity Herpes Encephalitis Homocystinuria Huntington's Disease Hyperparathyroidism Hypertensive Encephalopathy Hyperthyroidism Hypoparathyroidism Hypothyroidism Kidney Failure Klinefelter's Syndrome Liver Failure Lyme Disease Ménière's Syndrome Menopause Metachromatic Leukodystrophy Migraine Mitral Valve Prolapse Multiple Sclerosis Myasthenia Gravis Neurocutaneous Disorders Normal-Pressure Hydrocephalus Parasitism Parkinson's Disease Pellagra Pernicious Anemia Pheochromocytoma Pneumonia Polycystic Ovary Syndrome Porphyria Postoperative Delirium Premenstrual Syndrome Prion Disease Progressive Supranuclear Palsy Protein Energy Malnutrition Pulmonary Thromboembolism Rheumatoid Arthritis Sensory Deficit Sickle-Cell Disease Sleep Apnea Substance Intoxication and Withdrawal Syphilis Systemic Infection Systemic Lupus Erythematosus Thiamine Deficiency Traumatic Brain Injury Wilson's Disease III. Symptom Summaries

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Book SynopsisThis trusted practitioner resource and course text is grounded in James Morrison's experience with more than 15,000 mental health patients. Morrison provides a complete framework for interviewing adult patients about their current symptoms, personal and family history, mental status, behavioral risks, and other relevant issues. He offers guidance for selecting the best strategy for any clinical situation, building rapport, overcoming common challenges, and communicating findings. Appendices include a detailed semistructured interview and a self-assessment tool for interviewers, both with permission to photocopy. Purchasers also get access to a Web page where they can download and print the reproducible materials in a convenient 8 1/2 x 11 size. New to This Edition *Revised throughout for DSM-5. *Updated resources and suggested readings. See also Morrison's DSM-5-TR Made Easy, which explains DSM diagnoses in clear language, illustrated with vivid case Trade Review"An absolute 'must read' for any clinician at any level of experience. This clearly written, highly practical, step-by-step guide to conducting the first interview is filled with wisdom. Morrison is sensitive to and respectful of the patient while recognizing the clinician's need to get as much information as possible. The Appendices are invaluable. I cannot think of another book that comes close to this masterpiece. Thank you, Dr. Morrison, for providing this essential guide."--Robert L. Leahy, PhD, Director, American Institute for Cognitive Therapy; Department of Psychiatry, Weill Cornell Medical College "With pressure to improve quality, availability, and the economic value of mental health care, an effective, efficient start to the therapeutic process is more important than ever. The First Interview, Fourth Edition, addresses the reality that whatever the therapist’s orientation, a successful therapeutic alliance depends on the first encounter. This gives the book universal appeal and will benefit novice and seasoned therapists alike. Science and personal experience are woven into a seamless work that reads like common sense but is based on a substantial body of evidence. In an easy-to-read, conversational tone, Morrison conveys empathic interviewing techniques that can win patients' trust and allow them to share the most intimate life details."--Gary J. Kennedy, MD, Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine and Montefiore Medical Center "As a clinician educator who teaches interviewing, I have been searching for accessible reading material that incorporates DSM-5 and is appropriate for medical students, psychiatry residents, and multidisciplinary mental health care providers. My search is over! This book integrates DSM-5 and the latest research on interviewing without compromising the art of clinical care. Rather than rigidly applying diagnostic categories or theoretical frameworks, Morrison helps clinicians become attuned to the nuances of the interview in a way that will make patients feel heard and understood. I know that my patients and my trainees' future patients will receive more thorough, compassionate care as a result of the abundant clinical insights in this book."--Alana Iglewicz, MD, Department of Psychiatry, University of California, San Diego "Morrison has written one of the most comprehensive texts on the principles, techniques, and practice of initial interviewing. This book is indispensable for students first learning to work with clients, and is a valuable reference for experienced practitioners wishing to enhance their interviewing skills. Morrison presents sound and practical methods for establishing a warm and empathic therapeutic relationship, which in turn will help students and practitioners productively work with sensitive material."--Roy Jerome, PhD, Department of Psychiatry, Icahn School of Medicine at Mount Sinai -Table of ContentsIntroduction: What Is Interviewing? 1. Openings and Introductions 2. Chief Complaint and Free Speech 3. Developing Rapport 4. Managing the Early Patient Interview 5. History of the Present Illness 6. Getting the Facts about the Present Illness 7. Interviewing about Feelings 8. Personal and Social History 9. Sensitive Subjects 10. Control of the Later Interview 11. Mental Status Exam I: Behavioral Aspects 12. Mental Status Exam II: Cognitive Aspects 13. Signs and Symptoms in Areas of Clinical Interest 14. Closure 15. Interviewing Informants 16. Meeting Resistance 17. Special or Challenging Patient Behaviors and Issues 18. Diagnosis and Recommendations 19. Sharing Your Findings with the Patient 20. Communicating Your Findings to Others 21. Troubleshooting Your Interview Appendix A. Summary of the Initial Interview Appendix B. Descriptions of Selected Disorders Appendix C. Sample Interview, Written Report, and Formulation Appendix D. A Semistructured Interview Appendix E. Assessing Your Interview Appendix F. Bibliography and Recommended Reading

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Book SynopsisAuthoritative and comprehensive, this volume provides a contemporary psychodynamic perspective on frequently encountered psychological disorders in adults, children, and adolescents. Leading international authorities review the growing evidence base for psychoanalytic theories and therapeutic models. Chapters examine the etiology and psychological mechanisms of each disorder and thoroughly describe effective treatment strategies. Highly accessible, the book is richly illustrated with clinical case material. It demonstrates ways in which psychodynamic theory and therapy are enhanced by integrating ideas and findings from neuroscience, social and personality psychology, cognitive-behavioral therapy, and other fields. WinnerâGoethe Award for Psychoanalytic and Psychodynamic ScholarshipTrade Review"Bringing together some of our most distinguished psychoanalytic clinicians and researchers, this volume is a rare treasure trove of contemporary psychodynamic thinking and practice rooted in an evidence-based framework. It is set to become essential reading for mental health professionals in training and beyond."--Alessandra Lemma, DClinPsych, Visiting Professor, Psychoanalysis Unit, University College London, United Kingdom "This magnificent handbook not only demonstrates the tremendous richness of psychodynamic thinking about psychopathology, but also links it to empirical research and to neighboring disciplines like personality and social psychology, psychiatry, and neuroscience. I highly recommend this unique volume to anyone interested in the empirical validation of contemporary psychodynamic concepts."--Stephan Doering, MD, Professor and Director, Department of Psychoanalysis and Psychotherapy, Medical University of Vienna, Austria "From stellar editors and contributors, this impressive volume is a thoughtful gift to the field. Its perspectives on psychopathology are cutting edge and empirically supported. Readers from graduate students to senior clinicians and researchers will find this book invaluable."--J. Christopher Muran, PhD, Derner Institute of Advanced Psychological Studies, Adelphi University; Director, Mount Sinai Beth Israel Psychotherapy Research Program -The greatest contribution of this volume is its in-depth empirical evaluation of the many theoretical and clinical concepts it presents….Can promote the reintegration of psychodynamic principles into the general mental health field and encourage the further development of an empirical basis for psychodynamic constructs and techniques.--Journal of the American Psychoanalytic Association, 08/01/2016Table of ContentsI. Theoretical Background 1. Theoretical and Empirical Foundations of Contemporary Psychodynamic Approaches, Patrick Luyten, Linda C. Mayes, Sidney J. Blatt, Mary Target, & Peter Fonagy 2. Attachment-Related Contributions to the Study of Psychopathology, Mario Mikulincer & Phillip R. Shaver 3. The Developmental Perspective, Norka Malberg & Linda C. Mayes 4. Neuroscience and Psychoanalysis, Andrew J. Gerber, Jane Viner, & Joshua Roffman 5. The Psychodynamic Approach to Diagnosis and Classification, Patrick Luyten & Sidney J. Blatt 6. Defenses as a Transdiagnostic Window on Psychopathology, Robert J. Waldinger & Marc S. Schulz II. Psychopathology in Adults 7. Depression, Sidney J. Blatt 8. Generalized Anxiety Disorder and Other Anxiety Disorders, Fredric N. Busch & Barbara L. Milrod 9. Trauma, Jon G. Allen & Peter Fonagy 10. Obsessive–Compulsive Disorder, Guy Doron, Mario Mikulincer, Michael Kyrios, & Dar Sar-El 11. Substance Use Disorders, William H. Gottdiener & Jesse J. Suh 12. Eating Disorders, Heather Thompson-Brenner & Lauren K. Richards 13. Psychosis, Susanne Harder & Bent Rosenbaum 14. Functional Somatic Disorders, Patrick Luyten, Manfred Beutel, & Golan Shahar 15. Personality Disorders, Kevin B. Meehan & Kenneth N. Levy 16. Dependent Personality Disorder, Robert F. Bornstein 17. Borderline Personality Disorder, John F. Clarkin, Peter Fonagy, Kenneth N. Levy, & Anthony Bateman III. Psychopathology in Childhood and Adolescence 18. Child–Parent Psychotherapy in the Treatment of Infants and Young Children with Internalizing Disorders, Maria S. St. John & Alicia F. Lieberman 19. Conduct Disorders, Jonathan Hill & Helen Sharp 20. Attachment Disorders, Miriam Steele & Howard Steele 21. Reflective and Mindful Parenting: A New Relational Model of Assessment, Prevention, and Early Intervention, John Grienenberger, Wendy Denham, & Diane Reynolds 22. Working with Families, Trudie Rossouw IV. Process and Outcome in Psychodynamic Psychotherapies 23. Efficacy of Psychodynamic Psychotherapy in Specific Mental Disorders: An Update, Falk Leichsenring, Johannes Kruse, & Sven Rabung 24. Beyond Transference: Fostering Growth through Therapeutic Immediacy, Jared A. DeFife, Mark J. Hilsenroth, & Klara Kuutmann 25. Future Perspectives, Linda C. Mayes, Patrick Luyten, Sidney J. Blatt, Peter Fonagy, & Mary Target

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Book SynopsisAcclaimed as a text and professional development tool, this user-friendly resource has now been revised and updated, and offers expanded coverage of collaborative action research (CAR) and participatory action research (PAR). Preservice and inservice educators get crucial step-by-step guidance for conducting classroom- and school-based studies to improve their instructional practices. Organized to mirror the full cycle of action research, the book provides balanced coverage of qualitative, quantitative, and mixed methods approaches. Vivid vignettes and examples illustrate research approaches for a range of teaching and learning situations, school subjects, and age groups (PreK-12). Readers learn how research approaches are driven by the research question, as well as how to develop data collection strategies; design and/or evaluate assessment tools; interpret, analyze, report, and implement study results; and design a new cycle of research that builds on the previous one.<Trade Review"A solid overview of the essential components of action research, presented in a scholarly yet reader-friendly way. This text is excellent for our Master of Literacy program. It clearly depicts the six cyclical steps of action research, showing how research can continuously build our understanding of what works and what needs to be changed or adjusted. Unlike other action research texts that align only with qualitative research, the book discusses fundamentals of both qualitative and quantitative methods. The authors' emphasis on using the research questions to determine the research method(s) acknowledges the complexity of practitioner-based research. Practical and empowering, this book describes not only how to identify problems in educational settings, but also how to seek solutions through the cycle of research."--Cheryl A. Kreutter, PhD, School of Education, State University of New York at Geneseo "I used this book for several years as the primary text for an online graduate course, Action Research, which serves as a capstone for master's of education students. From the opening pages, the authors set the stage for understanding action research as an important approach to making classroom decisions based on systematically collected data. The pedagogical features such as vignettes and exercises are a strength of the book. There is a clear attempt to access textual, visual, and hands-on channels of learning. Self-quizzes allow for guided review."--John H. Yoder, PhD, Core Faculty in Education (retired), Concordia University–Portland "I have reviewed a number of action research texts, and, time and again, I return to Efron and Ravid’s book. It is simply the best available. With excellent content and depth, the text guides educators to conduct cycles of inquiry in their schools. It includes rich examples, tables, and figures to illustrate key concepts, as well as checklists to support action researchers."--Kimberly Kappler Hewitt, PhD, Division of Research, Discovery, and Innovation, School of Education, University of North Carolina at Greensboro "This is an excellent introductory text for the novice action researcher. The authors cover both qualitative and quantitative methods and offer advice on using already existing assessment data in action research studies. The text is practical and applicable to a wide variety of educational contexts."--Linnea Rademaker, PhD, School of Educational Leadership, Abilene Christian University "The book contains everything that I need in terms of content--it is a great introduction to action research. The writing style is its biggest strength. Many students are nervous about beginning to do research, and this book helps by presenting a step-by-step approach."--Eugene Geist, PhD, Department of Teacher Education, Ohio University-If you are teaching a research class to novice researchers, especially those in education, I would highly recommend this book for its practical approach, and the emphasis on writing and the use of assessment data. Teachers are often overwhelmed with available data in their classrooms and schools/m-/understanding as well as the data. This book provides much needed practical instructions for both issues. (on the first edition)--Inquiry in Education, 7/1/2013Table of Contents1. Introduction 2. Choosing and Learning about Your Research Topic 3. Approaches to Action Research 4. Developing a Plan of Action 5. Data Collection Tools 6. Using Assessment Data in Action Research 7. Data Analysis and Interpretation 8. Writing, Implementing, and Sharing the Research Findings References Author Index Subject Index

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisEffective research in educational settings requires collaboration between researchers and school-based practitioners to codesign instruction and assessment, analyze findings to inform subsequent iterations, and make thoughtful revisions. This innovative reference and course text examines the theory and practice of design-based research (DBR), an important methodology for conducting studies in authentic educational contexts. Leading experts provide specific examples of high-quality DBR addressing different research foci, grade levels, and subject areas (literacy/English language arts, math, and science). Applications are presented for curriculum development, intervention, assessment, and digital contexts, as well as teaching second-language learners. Also addressed is DBRâs role in educator preparation, professional development, dissertation research, and technical education.Trade Review"Why DBR? This book with chapters by experienced researchers in the field will guide you through all you need to know about this growing methodology in one place. Chapters cover what DBR is, how to do it, and specific applications. This book is suitable and informative for those just being introduced to the field, as well as for those of us who have been using DBR for years."--Diane Jass Ketelhut, EdD, Department of Teaching and Learning, Policy and Leadership, University of Maryland, College Park "Is it worth reading an entire book on a single research methodology? Absolutely. DBR merits extended attention given its versatility, its complexity, and, especially, its potential to bridge the notorious gap between research and practice. The book offers concrete, accessible guidance on the process of conducting DBR and shares examples of findings from DBR investigations in a range of educational domains and contexts. Graduate students will particularly appreciate the chapter on writing a DBR dissertation, and all readers will be inspired to include this approach in their methodological repertoires."--Nell K. Duke, EdD, Literacy, Language, and Culture concentration and the Combined Program in Education and Psychology, University of Michigan "DBR in authentic contexts is a crucial activity for scholars who wish to overcome the global challenges in education that we now confront. This important book describes the contributions of DBR to the planning and development of effective collaborative research in schools--a crucial stage in the continuum from early pilot studies to randomized clinical trials. The volume provides important insights for scholars, practitioners, and policymakers."--Chris Dede, EdD, Timothy E. Wirth Professor in Learning Technologies, Harvard Graduate School of Education "This book pairs thorough discussions of what DBR is with detailed, informative descriptions of a variety of DBR projects. The power of DBR lies in its focus on research projects that have real-world impact. This book shows how to involve teachers as professional collaborators and carry out design experiments in naturalistic settings."--Koeno Gravemeijer, PhD, School of Education (Emeritus), Eindhoven University of Technology, The Netherlands "Having taught a doctoral-level DBR course multiple times, I am delighted to finally see an edited volume that discusses the charms and challenges of the approach and shows what DBR looks like in a variety of content areas and contexts. This book will be of value to researchers hoping to learn more about DBR, those who are already engaged in it and seek to disseminate their work, and those looking for support in furthering the method in the field of education."--Jacquelynn A. Malloy, PhD, Department of Teaching and Learning, Clemson University-Table of ContentsI. Understanding Design-Based Research 1. Design-Based Research in Educational Settings: Motivations, Crosscutting Features, and Considerations for Design, Melissa Campanella & William R. Penuel 2. Addressing Publication Challenges in Design-Based Research, Margret Hjalmarson, Allison Ward Parsons, Seth A. Parsons, & Amy C. Hutchison II. Design-Based Research and Curriculum Development 3. Combining Curriculum and Teacher Development through Design Research, Jan van den Akker & Nienke Nieveen 4. Curriculum Development in Science, Kalle Juuti & Jari Lavonen 5. Classroom Design-Based Research: Designing for Proportional Reasoning in Mathematics Education, Michelle Stephan 6. Curriculum Development of Reading and Writing in the Middle Grades, Zoi A. Philippakos & Charles A. MacArthur III. Design-Based Research and Specific Applications 7. Literacy Is Transformative: Secondary Reading Interventions Using Design-Based Research, Alejandro Gonzalez, Nancy Frey, Douglas Fisher, & Diane Lapp 8. Collaborative Design to Support Digital Literacies across the Curriculum, Kelly Chandler-Olcott, Sharon Dotger, Kathleen A. Hinchman, Heather Waymouth, & Keith O. Newvine 9. Multilingual Students and Design-Based Research: Developing Opportunities in Partnerships, Ryan McCarty, Tim Pappageorge, & Claudia Rueda-Alvarez 10. Using Design-Based Research to Develop a Formative Assessment Tool, Kristi Tamte Bergeson IV. Design-Based Research and Teacher-Researchers 11. Professional Development on Genre-Based Strategy Instruction on Writing, Zoi A. Philippakos 12. Improving Disciplinary Literacy Teaching: A Formative Experiment Exploring Professional Development in Disciplinary Settings, Phillip Wilder, Emily Howell, Lorraine Jacques, Susan Cridland-Hughes, & Mary-Celeste Schreuder 13. Purposeful Clinical Practices in Teacher Preparation through Design-Based Research, Anthony Pellegrino 14. Graduate Students Writing Design-Based Research Dissertations, Susan McKenney & Thomas Reeves 15. Fostering Techno-Mathematical Literacies in Higher Technical Education: Reflections on Challenges and Successes of Design-Based Implementation Research, Nathalie J. van der Wal, Arthur Bakker, Albert Moes, & Paul Drijvers Index

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Book SynopsisWritten from an interpretive and constructionist perspective, this insightful book explores how to conduct case study research focusing on the lived experience of those in the case. Helen Simons shines a spotlight on the use of art forms and story in case study research alongside other qualitative methods that advance intuitive understanding and inclusion. Underpinning this focus are epistemic justice and democratic ethics. In a lively, personal style, Simons distills expertise and practical wisdom gained over decades of conducting case study research of programs, policies, and institutions. Chapters consider how to design, conduct, and interpret case study research; write up cases for different audiences; assure validity and quality; and generalize from a single case. Helpful features include examples, summaries, practical tips, âœPauses to Reflect,â and annotated suggestions for further reading.

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Book SynopsisThe most user-friendly and authoritative resource on missing data has been completely revised to make room for the latest developments that make handling missing data more effective. The second edition includes new methods based on factored regressions, newer model-based imputation strategies, and innovations in Bayesian analysis. State-of-the-art technical literature on missing data is translated into accessible guidelines for applied researchers and graduate students. The second edition takes an even, three-pronged approach to maximum likelihood estimation (MLE), Bayesian estimation as an alternative to MLE, and multiple imputation. Consistently organized chapters explain the rationale and procedural details for each technique and illustrate the analyses with engaging worked-through examples on such topics as young adult smoking, employee turnover, and chronic pain. The companion website (www.appliedmissingdata.com) includes data sets and analysis examples from the bTrade Review"The second edition of Applied Missing Data Analysis is a bold, top-to-bottom revision that makes a phenomenal book even better. Enders offers a completely updated treatment, including such important topics as models with continuous and categorical variables, Bayesian missing data approaches, methods for missing not at random processes, and even a guide to how researchers should report their missing data analyses. Beyond the central focus on missing data, I can already hear myself saying, 'Go read Enders's book!' to students and colleagues with questions about how maximum likelihood estimation works, the logic of Markov Chain Monte Carlo methods, and so much more. This book is exemplary teaching that you can hold in your hands. I will recommend it with the greatest enthusiasm to students, faculty, and applied researchers alike for many years to come."--Gregory R. Hancock, PhD, Professor and Distinguished Scholar-Teacher, Department of Human Development and Quantitative Methodology, University of Maryland, College Park "Approaches for dealing with missing data have progressed greatly in the statistical and methodological literatures, and the second edition of this exemplary book thoroughly presents and synthesizes these developments. The book makes sophisticated statistics amazingly accessible and offers a great deal to a wide audience, including statisticians, data analysts, substantive researchers, and quantitative students. I learn something new (or better understand something I thought I knew) every time I pick up this book! The presentation of how to report results from a missing data analysis, which gives explicit examples of such reporting for a wide variety of scenarios, is particularly useful. With an abundance of examples, figures, and illustrations to enhance the crystal-clear exposition, this is the 'go-to' book for dealing with missing data in statistical modeling."--Donald Hedeker, PhD, Department of Public Health Sciences, University of Chicago "Thorough, cutting-edge, and far and away the clearest text available on missing data analysis. Written by a world-renowned expert who is a gifted instructor, this book is accessible enough for applied researchers with introductory statistics and regression knowledge, is an outstanding text for a missing data course, or can be used to fill gaps in methodologists’ understanding of the notoriously opaque missing data literature. For researchers who learned 'modern' missing data-handling methods years ago--much has changed. For instance, the second edition will bring you up to speed on how to accommodate missingness in conjunction with non-normal and discrete outcomes, nonlinear and interactive relationships, and multilevel structures; choose among non-model-based versus model-based multiple imputation methods; and conceptualize and implement sensitivity analyses to assess the impact of alternative missing data assumptions. Reading this book feels like being guided by the author through a comprehensive one-on-one workshop. A gift to the field!"--Sonya K. Sterba, PhD, Professor of Psychology and Director, Quantitative Methods Program, Vanderbilt University “Simply stated, this is the best textbook available on missing data analysis. The book provides comprehensive coverage, is highly accessible, and is written by one of the experts in the field. The concepts involved in missing data analysis are complex, and it is obvious that Enders takes the 'teaching mission' seriously. The writing is clear, the figures and tables are very helpful in promoting understanding, and the simulations developed for the text are helpful in conveying the strengths and weaknesses of various missing data treatments. The excellent companion website provides important, updated resources for teaching and learning. The software scripts available on the website are very useful for researchers wishing to apply the missing data methods to real data."--Keenan A. Pituch, PhD, Edson College of Nursing and Health Innovation, Arizona State University-The book is well written….The author successfully achieved the goal of helping the reader to become familiar with basic concepts in missing data analysis procedures, and to feel comfortable using these procedures in a variety of practical and social science applications. It contains very useful examples and illustrations in the applied social sciences. (on the first edition)--American Statistician, 08/01/2011Table of Contents1. Introduction to Missing Data 1.1 Chapter Overview 1.2 Missing Data Patterns 1.3 Missing Data Mechanisms 1.4 Diagnosing Missing Data Mechanisms 1.5 Auxiliary Variables 1.6 Analysis Example: Preparing for Missing Data Handling 1.7 Older Missing Data Methods 1.8 Comparing Missing Data Methods via Simulation 1.9 Planned Missing Data 1.10 Power Analyses for Planned Missingness Designs 1.11 Summary and Recommended Readings 2. Maximum Likelihood Estimation 2.1 Chapter Overview 2.2 Probability Distributions versus Likelihood Functions 2.3 The Univariate Normal Distribution 2.4 Estimating Unknown Parameters 2.5 Getting an Analytic Solution 2.6 Estimating Standard Errors 2.7 Information Matrix and Parameter Covariance Matrix 2.8 Alternative Approaches to Estimating Standard Errors 2.9 Iterative Optimization Algorithms 2.10 Linear Regression 2.11 Significance Tests 2.12 Multivariate Normal Data 2.13 Categorical Outcomes: Logistic and Probit Regression 2.14 Summary and Recommended Readings 3. Maximum Likelihood Estimation with Missing Data 3.1 Chapter Overview 3.2 The Multivariate Normal Distribution Revisited 3.3 How Do Incomplete Data Records Help? 3.4 Standard Errors with Incomplete Data 3.5 The Expectation Maximization Algorithm 3.6 Linear Regression 3.7 Significance Testing 3.8 Interaction Effects 3.9 Curvilinear Effects 3.10 Auxiliary Variables 3.11 Categorical Outcomes 3.12 Summary and Recommended Readings 4. Bayesian Estimation 4.1 Chapter Overview 4.2 What Makes Bayesian Statistics Different? 4.3 Conceptual Overview of Bayesian Estimation 4.4 Bayes’ Theorem 4.5 The Univariate Normal Distribution 4.6 MCMC Estimation with the Gibbs Sampler 4.7 Estimating the Mean and Variance with MCMC 4.8 Linear Regression 4.9 Assessing Convergence of the Gibbs Sampler 4.10 Multivariate Normal Data 4.11 Summary and Recommended Readings 5. Bayesian Estimation with Missing Data 5.1 Chapter Overview 5.2 Imputing an Incomplete Outcome Variable 5.3 Linear Regression 5.4 Interaction Effects 5.5 Inspecting Imputations 5.6 The Metropolis–Hastings Algorithm 5.7 Curvilinear Effects 5.8 Auxiliary Variables 5.9 Multivariate Normal Data 5.10 Summary and Recommended Readings 6. Bayesian Estimation for Categorical Variables 6.1 Chapter Overview 6.2 Latent Response Formulation for Categorical Variables 6.3 Regression with a Binary Outcome 6.4 Regression with an Ordinal Outcome 6.5 Binary and Ordinal Predictor Variables 6.6 Latent Response Formulation for Nominal Variables 6.7 Regression with a Nominal Outcome 6.8 Nominal Predictor Variables 6.9 Logistic Regression 6.10 Summary and Recommended Readings 7. Multiple Imputation 7.1 Chapter Overview 7.2 Agnostic versus Model-Based Multiple Imputation 7.3 Joint Model Imputation 7.4 Fully Conditional Specification 7.5 Analyzing Multiply-Imputed Data Sets 7.6 Pooling Parameter Estimates 7.7 Pooling Standard Errors 7.8 Test Statistic and Confidence Intervals 7.9 When Might Multiple Imputation Give Different Answers? 7.10 Interaction and Curvilinear Effects Revisited 7.11 Model-Based Imputation 7.12 Multivariate Significance Tests 7.13 Summary and Recommended Readings 8. Multilevel Missing Data 8.1 Chapter Overview 8.2 Random Intercept Regression Models 8.3 Random Coefficient Models 8.4 Multilevel Interaction Effects 8.5 Three-Level Models 8.6 Multiple Imputation 8.7 Joint Model Imputation 8.8 Fully Conditional Specification Imputation 8.9 Maximum Likelihood Estimation 8.10 Summary and Recommended Readings 9. Missing Not at Random Processes 9.1 Chapter Overview 9.2 Missing Not at Random Processes Revisited 9.3 Major Modeling Frameworks 9.4 Selection Models for Multiple Regression 9.5 Model Comparisons and Individual Influence Diagnostics 9.6 Selection Model Analysis Examples 9.7 Pattern Mixture Models for Multiple Regression 9.8 Pattern Mixture Model Analysis Examples 9.9 Longitudinal Data Analyses 9.10 Diggle–Kenward Selection Model 9.11 Shared Parameter (Random Coefficient) Selection Model 9.12 Random Coefficient Pattern Mixture Models 9.13 Longitudinal Data Analysis Examples 9.14 Summary and Recommended Readings 10. Special Topics and Applications 10.1 Chapter Overview 10.2 Descriptive Summaries, Correlations, and Subgroups 10.3 Non-Normal Predictor Variables 10.4 Non-Normal Outcome Variables 10.5 Mediation and Indirect Effects 10.6 Structural Equation Models 10.7 Scale Scores and Missing Questionnaire Items 10.8 Interactions with Scales 10.9 Longitudinal Data Analyses 10.10 Regression with a Count Outcome 10.11 Power Analyses for Growth Models with Missing Data 10.12 Summary and Recommended Readings 11. Wrap-Up 11.1 Chapter Overview 11.2 Choosing a Missing Data-Handling Procedure 11.3 Software Landscape 11.4 Reporting Results from a Missing Data Analysis 11.5 Final Thoughts and Recommended Readings Appendix. Data Set Descriptions Author Index Subject Index About the Author

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Book SynopsisFrom the founder of empowerment evaluation (EE), a framework uniquely suited to advancing social justice causes, this book explains the theories, principles, and steps of conducting EE from scratch or within a preexisting evaluation or work plan. David M. Fetterman describes how EE enables program planners and participants to define their mission or purpose, take stock of how well they are doing, and plan for the future to achieve self-determined goals. EEs of two large programs (Feeding America and USAID/REACH) are discussed in depth; other EE case examples address such topics as raising test scores in impoverished and rural schools and bridging the digital divide in communities of color. User-friendly features include chapters on conducting EE remotely and frequently asked questions, as well as illuminating sidebars and glossaries of acronyms and concepts/terms.Trade Review"This is a rare text in so many ways. It is real-world and integrative, drawing on theories of cultural transformation and social justice while offering practical insights into how self-determination, self-efficacy, and transformative change can be achieved within existing programs and organizations. The hands-on guidance offered in this book effectively advances the EE paradigm. Fetterman's use of international settings and organizational case studies brings these sophisticated transformation concepts to life for all readers, transcending national borders. Fetterman has given us the insight and tools to be social justice advocates and change agents, which is no small contribution. This text should be part of every evaluation program; it will be especially helpful when students advance to fieldwork with actual clients and key stakeholders."--Gary J. Skolits, EdD, Department of Educational Leadership (Emeritus), University of Tennessee "This remarkable book tells us clearly how EE works. Fetterman provides step-by-step instructions and tools for facilitating stakeholder involvement in evaluation in pursuit of social justice. The book discusses concepts and principles of real-world EE. I appreciated the lengthy examples and enriching case studies, as well as the sidebars and glossaries."--Apollo M. Nkwake, PhD,author of Working with Assumptions in International Development Program Evaluation "A vital resource for anyone looking to build evaluation capacity, facilitate change, and contribute to transformation. A leader in evaluation, Fetterman is uniquely situated to contribute to our understanding of tools and strategies for pursuing social justice. The book is special in its applicability in both the classroom and the field."--Kelly Melekis, MSW, PhD, Department of Social Work, University of Vermont-Table of ContentsPreface Glossary of Acronyms 1. Introduction: From Inception to Institutionalization 2. Essential Features: Theories, Concepts, Principles, and Steps 3. Integrating Empowerment Evaluation within a Preexisting Evaluation and Recognizing Donors as Change Agents: Feeding America’s Fight for Food Justice in the United States 4. Integrating Empowerment Evaluation within a Preexisting Workplan and Celebrating Donors as Change Agents: USAID/REACH’s Initiative to Eliminate Tuberculosis in India 5. Tech Tools: Conducting Empowerment Evaluation Remotely 6. Empowerment Evaluation: Frequently Asked Questions 7. Conclusion: Commitments to Social Justice Glossary of Terms References Index About the Author

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Book SynopsisIn this uniquely integrative book, Paul L. Wachtel describes powerful clinical strategies to make roomfor aspects of the self that were sidetracked in the course of development. Wachtel explores how early attachment experiences can lead people to turn away from certain thoughts and feelings, building a sense of self and ways of interacting on only a limited range of adaptive resources. His approach draws on psychodynamic, humanistic, systemic, and acceptance-centered cognitive-behavioral perspectives, as well as attention to the impact of race, class, and culture. Filled with rich case material, the book illuminates how a therapeutic approach anchored in the present can help heal the wounds of the past. See also Wachtel's Therapeutic Communication, Second Edition: Knowing What to Say When, as well as Mastering the Clinical Conversation: Language as Intervention, by Matthieu Villatte, Jennifer L. Villatte, and Steven C. Hayes.Trade Review"Wachtel eloquently presents a wonderful integrative approach in which making room is the pivotal process. Making room does not involve interpreting, modifying, or educating; it is about helping the person gain access to parts of self they have shied away from. This is the work on theoretical integration that the field has been waiting for."--Leslie S. Greenberg, PhD, Distinguished Research Professor Emeritus of Psychology, York University, Canada "This is a groundbreaking volume from a giant of psychotherapy who has long sought ways to build bridges between psychodynamic thinking and other traditions. Wachtel's focus on making room challenges some aspects of traditional psychodynamic approaches; at the same time, it makes the psychodynamic methods described here immediately accessible and valuable to practitioners of humanistic approaches, third-wave cognitive-behavioral therapy, or many other varieties of modern psychotherapy. The book is brilliant and challenging--I highly recommend it."--Steven C. Hayes, PhD, Foundation Professor of Psychology Emeritus, University of Nevada, Reno; codeveloper of Acceptance and Commitment Therapy "A necessary companion for practicing clinicians and students alike. Wachtel's book is like a microfiber cloth to clean our psychotherapist-lenses. It highlights the delicate and dynamic relationship between therapist and patient--and is a lesson on how to build a sturdy enough room to house it."--Esther Perel, MA, LMFT, private practice, New York City; podcast host, Where Should We Begin? "This readable book embodies its own subject matter--expanding therapeutic conversations rather than forcing them into the narrow paradigms into which contemporary researchers and clinicians are socialized. Whether trained in DSM diagnoses, symptom-focused manuals, or authoritarian rules of interpretation, mental health professionals will find Wachtel’s book both incisive and liberating. Long admired for his deeply knowledgeable, respectful treatment of competing ideas, Wachtel breaks new ground in this integrative discourse on psychological healing. Beginning therapists will benefit from Wachtel's clarity, practicality, and humanity; seasoned clinicians will benefit from penetrating insights that support their best therapeutic instincts."--Nancy McWilliams, PhD, ABPP, Visiting Professor Emerita, Graduate School of Applied and Professional Psychology, Rutgers, The State University of New Jersey-Table of ContentsI. Introduction 1. Making Room for Thoughts and Feelings: Attachment, Self-Acceptance, and Emotional Immediacy 2. Silos, Stereotypes, and the Evolutionary Links between Diverse and Competing Approaches 3. What Is the Appropriate Evidence Base for Responsible Clinical Practice? II. Beyond Pathologizing: The Dialectics of Acceptance and Change 4. From Interpreting Wishes and Feelings to Making Room for Them: The Problem with Uncovering “the Truth” 5. The Roots of Pathologizing and Accusatory Interpretations 6. Anxiety, Exposure, and the Path to Self-Acceptance 7. Making Room in CBT: From Beck and Ellis to the Dialectics of Acceptance and Change III. Attachment and the Lifelong Dynamics of Development 8. Self-Acceptance and Self-Rejection: The Critical Impact of Attachment 9. Working in the Present on the Consequences of the Past IV. Living-in-the-World 10. Experiencing, Emotional Immediacy, and Self-in-Action 11. Living in Contexts: From the Relational Matrix to the Impact of Culture and Society 12. The Many Faces of Psychotherapy References Index

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Book SynopsisDesigned to help students make the leap from learning about research to doing research, this manual provides an easy-to-understand walkthrough of the entire research process, from selecting a topic and conducting a literature review through presenting an APA-style paper or presentation. All of the 15 cross-disciplinary labs included are appropriate for use in the social, behavioral, and health sciences, and follow a consistent format: objective, description of a journal article, canned data, examples of what output should look like, pointers on interpreting the output, and a suggested activity for those who wish to collect their own data.Table of ContentsPART I: Before You Collect Data LAB 1. Finding a Topic, Finding Sources, and Critically Reading Appropriate Articles Finding a Topic What Are the Steps of a Research Project? Tips for Finding Sources How to Read an Article Closure If You Want to Go Further . . . Secondary Analyses of Large Data Sets Available Online LAB 2: How to Write a Literature Review The Literature Review APA Style If You Want to Go Further . . . Writing “Good” LAB 3: After the Literature Review: Theory > Hypothesis > Design > Analysis > Results > Interpretation The Logic Behind the Research Theory > Hypothesis > Design > Analysis: Method Section Theory > Hypothesis > Design > Analysis > Results Theory > Hypothesis > Design > Analysis > Results > Interpretation If You Want to Go Further . . . Cultural Considerations Pick a Card, Any Card . . . LAB 4: Ethics of Research How to Treat Participants (Human or Otherwise) The Ethics of Reporting Research If You Want to Go Further . . . The Role of the IRB Preparing a Proposal for the IRB What to Expect Once Your Project Has Been Approved PART II: Collecting Data - Research Designs and Tools LAB 5: Qualitative Research Qualitative Research: What Is It, and What Do You Do With It? If You Want to Go Further . . . Content Analysis What’s the Point of All This Qualitative Information? Development of a Grounded Theory Communicating the Results LAB 6: Case Studies and Single-Subject Designs Case Study Versus Single-Subject Design Who Uses Behavior Modification? If You Want to Collect Your Own Data . . . It′s All About You If You Want To Go Further . . . Large-Scale Epidemiology: The Opposite Approach LAB 7: Surveys Types of Survey Questions Writing the Method If You Want To Collect Your Own Data . . . Distributing the Survey Informed Consent—Really, Really Important! Producing the Abbreviated Lab Report If You Want to Go Further . . . Developing the Survey LAB 8: Descriptive and Inferential Statistics Descriptive Versus Inferential Statistics Scales of Measurement T-Test Closure If You Want to Go Further . . . More About Effect Size Types of Effect Size Statistics How Big Is Big Enough? To Summarize Reviewing What You′ve Learned: Answer Key LAB 9: Correlational Design Experimental Versus Non-Experimental If You Want to Collect Your Own Data . . . Closure If You Want to Go Further . . . Partial Correlations LAB 10: Regression Analysis A Step Up Practice and Review Summing Up If You Want to Go Further . . . Hierarchical Regression LAB 11: Two-Group Designs The Two-Group Design If You Want to Collect Your Own Data . . . Be the Participant Levels of Processing Data If You Want to Go Further . . . Chi-Squared Analysis LAB 12: Multiple-Groups Designs Going Beyond the Two-Group Design If You Want to Collect Your Own Data . . . Cautions! Putting It All Together If You Want to Go Further . . . Categorical IVs and DVs in Regression Coding Categorical Predictor Variables for Regression Logistic Regression LAB 13: Factorial Designs Background Are We There Yet? More Practice With Interactions If You Want to Go Further . . . More About Testing Interactions What Happens With Categorical Predictors? What Happens With Repeated-Measures Data? Answers for More Practice With Interactions PART III: After Collecting Data LAB 14: Writing the Discussion Section, Sharing Your Findings Using a Poster or Oral Presentation Discussion Section Checklist Creating and Presenting a Poster Preparing an Oral Presentation of Your Findings Closure If You Want to Go Further . . . The Publication Process: What to Expect When You’re Submitting LAB 15: Tables and Figures Tables Figures How Do I Create a Figure? Using SPSS If You Want to Collect Your Own Data . . . If You Want to Go Further . . . A Few More (Optional) Things In Conclusion

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Book SynopsisAn Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical methods for exploring data, spotting unusual features, visualizing fitted models, and presenting results.The book is designed for advanced undergraduate and graduate students in the social and health sciences, epidemiology, economics, business, statistics, and biostatistics as well as researchers, methodologists, and consultants who can use the methods with their own data and analyses. Along with describing the necessary statistical theory, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to organize data, conduct an analysTrade Review"This is an excellent book, nearly encyclopedic in its coverage. I personally find it very useful and expect that many other readers will as well. The book can certainly serve as a reference. It could also serve as a supplementary text in a course on categorical data analysis that uses R for computation or—because so much statistical detail is provided—even as the main text for a course on the topic that emphasizes graphical methods."—John Fox, McMaster University"For many years, Prof. Friendly has been the most effective promoter in Statistics of graphical methods for categorical data. We owe thanks to Friendly and Meyer for promoting graphical methods and showing how easy it is to implement them in R. This impressive book is a very worthy addition to the library of anyone who spends much time analyzing categorical data." (Alan Agresti, Biometrics)Table of ContentsGetting Started: Introduction. Working with Categorical Data. Fitting and Graphing Discrete Distributions. Exploratory and Hypothesis-Testing Methods: Two-Way Contingency Tables. Mosaic Displays for n-Way Tables. Correspondence Analysis. Model-Building Methods: Logistic Regression Models. Models for Polytomous Responses. Loglinear and Logit Models for Contingency Tables. Extending Loglinear Models. Generalized Linear Models for Count Data.

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Book SynopsisConducting Research in Psychology: Measuring the Weight of Smoke provides students an engaging introduction to psychological research by employing humor, stories, and hands-on activities. Through its methodology exercises, learners are encouraged to use their intuition to understand research methods and apply basic research principles to novel problems. Authors Brett W. Pelham and Hart Blanton integrate cutting-edge topics, including implicit biases, measurement controversies, online data collection, and new tools for determining the replicability of a set of research findings. The Fifth Edition broadens its coverage of methodologies to reflect the types of research now conducted by psychologists. Two new chapters accommodate the needs of instructors who incorporate student research projects into their courses. Table of ContentsPreface About the Authors CHAPTER 1. How Do We Know? Introduction: What This Text Is About A Few Quick Tips for Using This Text Preamble for Chapter 1 A Brief History of Human Knowledge The Four Canons of Science Four Ways of Knowing About the World Summary Study Questions Notes CHAPTER 2. How Do We Find Out? The Logic, Art, and Ethics of Scientific Discovery The Logic of Scientific Discovery The Art of Scientific Discovery The Ethics of Scientific Discovery Summary Study Questions Notes CHAPTER 3. In a Nutshell: An Overview of Psychological Research Methods A Tale of Two Validities Three Requirements for Establishing Causality Experiments: Fulfilling Mill’s Requirements Passive Observational (Nonexperimental) Research Methods Trade-Offs Between Internal and External Validity GAGES: The “Big Five” of Worrisome Confounds External Validity and the OOPS! Heuristic Oops! He Did It Again: Maximizing External Validity in the Lab Gauging GAGES in Archival Studies of Social Cognition Summary Study Questions CHAPTER 4. Making It Happen: A Hands-On Guide to a First Research Project Everybody Dance Now Step 1: Hypothesis Generation Step 2: Operationalization (Design) Step 3: Permission Step 4: Execution (Data Collection) Step 5: Calculation (Data Analysis) Step 6: Communication Summary Study Questions Notes CHAPTER 5. Moving From Fact to Truth: Validity, Reliability, and Measurement Three Strange Stories Validity Reliability Reliability, Validity, and the “More Is Better” Rule Measurement Scales Summary Study Questions CHAPTER 6. Moving From Notions to Numbers: Psychological Measurement Converting Notions to Numbers: The Two Major Challenges The Response Translation Phase Putting It All Together: The EGWA Scale From Writing Questions to Creating Scales Summary Study Questions CHAPTER 7. How Do We Misinterpret? Common Threats to Validity One Strange and Lucrative Story People Are Different People Change The Process of Studying People Changes People Moving From Three Threats to Two: Confounds and Artifacts Summary Study Questions Note CHAPTER 8. Nonexperimental Research Designs Describing the World of a Single Participant: Case Studies Describing the State of the World at Large: Single-Variable Research Describing Associations: Multiple-Variable Research Archival Research Observational Research Confounds Can Be Measured, Too! Summary Study Questions Notes CHAPTER 9. Experience Carefully Planned: Experimental Research Designs A Wonderful Method A Brief History of True Experiments Strengths of True Experiments Are True Experiments Realistic? Is There a Recipe for Experimental Realism? Trade-Offs Between Internal and External Validity The “How-Tos” of Laboratory Studies Summary Study Questions Notes CHAPTER 10. Experience Carefully Exploited: Quasi-Experimental Research Designs One Very Old Story Why Quasi-Experiments? Kinds of Quasi-Experiments Comparability Patched-Up Designs When True Experiments and Quasi-Experiments Collide Summary Study Questions Notes CHAPTER 11. Choosing the Right Research Design One Obscure Movie One-Way Designs Factorial Designs Within-Subjects Designs Mixed-Model Designs Summary Study Questions Notes CHAPTER 12. A Brief Course in Statistics How Numbers and Language Revolutionized Human History Descriptive Statistics Inferential Statistics Things That Go Bump in the Light: Factors That Influence the Results of Significance Tests The Changing State of the Art: Alternate Perspectives on Statistical Hypothesis Testing Summary Study Questions Notes CHAPTER 13. Telling the World About It The Hourglass Approach to Empirical Research Papers Some Rules to Writing Research Papers How to Give a Good Talk in Psychology (by Daniel T. Gilbert) Have a Plan Tell the Plan Start at the Beginning Be Painfully Clear Talk About One Interesting Thing Take Charge of the Interaction End at the End Summary Study Questions Appendix 1: Hands-On Activities Hands-On Activity 1: Galileo’s Dice Hands-On Activity 2: Regression Toward the Mean Hands-On Activity 3: A Double-Blind Taste Test With Popular Colas Hands-On Activity 4: The Stroop Interference Effect Appendix 2: Methodology Exercises Methodology Exercise 1: Partial Correlation Methodology Exercise 2: Random Assignment Methodology Exercise 3: Interactions Methodology Exercise 4: Repeated Measures Designs Questions Appendix 3: Putting Your Knowledge to Work: 25 Methodology Problems 1. In Search of a Delicious, Low-Fat TV Show 2. Let’s Get Supernatural 3. Fly Away Home 4. Impressive Pickup Lines 5. Clever Who? 6. Life Sucks and So You Die 7. On the Drawbacks of Liking Yourself 8. The Early Bird Gets the Win? 9. Testosterone Makes Better Dive-Bombers 10. Working Your Fingers to the Dean’s List 11. To Thine Own Selves Be True 12. A Rosy Mood by Any Other Name? 13. EPSCOR: Do Fractions Have Denominators? 14. Sampling Student Opinion 15. Are You the Favorite Person of Anybody? 16. He May Be Small but He’s Slow 17. Everyone’s a Winner 18. Can a Couple of Beers Really Go Straight to Your Belly? 19. What’s in a Name? 20. Are You Threatening Me? 21.Genes, Schmenes 22. Do Car Thieves Really Love Old Hondas? 23. An Unbiased Assessment? 24. Mary, Mary, Quite the Centenarian? 25. Register on Time (The 11:59 Initiative) Appendix 4: An Example of an APA-Style Research Paper: Ethnicity and the Risk of Unwarranted Cesarean Birth in the United States Glossary References Name Index Subject Index

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Book SynopsisLab Manual for Psychological Research and Statistical Analysis serves as an additional resource for students and instructors in a research methods, statistics, or combined course where classroom and/or laboratory exercises are conducted. Packed with exercises, checklists, and how-to sections, this robust lab manual gives students hands-on guidance and practice for conducting and analyzing their own psychological research. Dawn M. McBride and J. Cooper Cutting provide students with additional opportunities for practice in a course with challenging material that requires practice and repetition for deeper understanding.Table of ContentsIntroduction for Instructors CHAPTER 1 • Psychological Research: The Whys and Hows of the Scientific Method and Statistics 1a: The Purpose of Statistics 1b: Science in the Media 1c: Understanding Your Data 1d: Displaying Distributions 1e: Making and Interpreting Graphs 1f: Setting up Your Data in SPSS: Creating a Data File 1g: Displaying Distributions in SPSS CHAPTER 2 • Developing a Research Question and Understanding Research Reports 2a: How to Read Empirical Journal Articles 2b: Reading Journal Articles—Mueller and Oppenheimer (2014) 2c: Reading Journal Articles—Roediger and Karpicke (2006) 2d: Reviewing the Literature 2e: Creating References 2f: APA Style 2g: APA-Style Manuscript Checklist CHAPTER 3 • Ethical Guidelines for Psychological Research 3a: Ethics 3b: Ethics in a Published Study 3c: Academic Honesty Guidelines—What Is (and Isn’t) Plagiarism 3d: Examples of Plagiarism 3e: Identifying and Avoiding Plagiarism CHAPTER 4 • Probability and Sampling 4a: Distributions and Probability 4b: Basic Probability 4c: Subject Sampling 4d: Sampling CHAPTER 5 • How Psychologists Use the Scientific Method: Data Collection Techniques and Research Designs 5a: Naturalistic Observation Group Activity 5b: Basics of Psychological Research 5c: Designing an Experiment Activity 5d: Research Design Exercise 5e: Design and Data Collection Exercise CHAPTER 6 • Descriptive Statistics 6a: Central Tendency: Comparing Data Sets 6b: Understanding Central Tendency 6c: Central Tendency in SPSS 6d: Describing a Distribution (Calculations by Hand) 6e: More Describing Distributions 6f: Descriptive Statistics With Excel 6g: Measures of Variability in SPSS CHAPTER 7 • Independent Variables and Validity in Research 7a: Identifying and Developing Hypotheses About Variables 7b: Independent and Dependent Variables 7c: Identifying Variables From Abstracts 7d: Identifying Variables From Empirical Articles 7e: Research Concepts: Designs, Validity, and Scales of Measurement 7f: Internal and External Validity CHAPTER 8 • One-Factor Experiments 8a: Bias and Control Exercise 8b: Experimental Variables 8c: Experiments Exercise 8d: Experimental Designs CHAPTER 9 • Hypothesis-Testing Logic 9a: Inferential Statistics Exercise 9b: Calculating z Scores Using SPSS 9c: The Normal Distribution 9d: z Scores and the Normal Distribution 9e: Hypothesis Testing With Normal Populations 9f: Hypothesis Testing With z Tests CHAPTER 10 • t Tests 10a: Hypothesis Testing With a Single Sample 10b: One-Sample t Test in SPSS 10c: One-Sample t Tests by Hand 10d: Related-Samples t Tests 10e: Related-Samples t Test in SPSS 10f: Independent Samples t Tests 10g: Hypothesis Testing—Multiple Tests 10h: More Hypothesis Tests With Multiple Tests 10i: t Tests Summary Worksheet 10j: Choose the Correct t Test 10k: Writing a Results Section From SPSS Output—t Tests CHAPTER 11 • One-Way Analysis of Variance 11a: One-Way Between-Subjects Analysis of Variance (Hand Calculations) 11b: One-Way Between-Subjects Analysis of Variance in SPSS 11c: Writing a Results Section From SPSS Output—Analysis of Variance 11d: Inferential Statistics and Analyses CHAPTER 12 • Correlation Tests and Simple Linear Regression 12a: Creating and Interpreting Scatterplots 12b: Understanding Correlations 12c: Correlations and Scatterplots in SPSS 12d: Computing Correlations by Hand 12e: Hypothesis Testing With Correlation Using SPSS 12f: Regression CHAPTER 13 • Chi-Square Tests 13a: Chi-Square Crosstabs Tables 13b: Chi-Square Hand Calculations From Crosstabs Tables 13c: Chi-Square in SPSS—Type in the Data 13d: Chi-Square in SPSS From a Data File CHAPTER 14 • Multifactor Experiments and Two-Way Analysis of Variance (Chapters 14 and 15) 14a: Factorial Designs 14b: Factorial Designs Article—Sproesser, Schupp, and Renner (2014) 14c: Factorial Designs Article—Farmer, McKay, and Tsakiris (2014) 14d: Describing Main Effects and Interactions 14e: Factorial Analysis of Variance 14f: Analysis of Variance Review 14g: Main Effects and Interactions in Factorial Analysis of Variance CHAPTER 15 • One-Way Within-Subjects Analysis of Variance 15a: One-Way Within-Subjects Analysis of Variance 15b: One-Way Within-Subjects Analysis of Variance in SPSS 15c: One-Way Within-Subjects Analysis of Variance Review CHAPTER 16 • Meet the Formulae and Practice Computation Problems 16a: Meet the Formula and Practice Problems: z Score Transformation 16b: Meet the Formula and Practice Problems: Single-Sample z Tests and t Tests 16c: Meet the Formula and Practice Problems: Comparing Independent Samples and Related Samples t Tests 16d: Meet the Formula and Practice Problems: One-Factor Between-Subjects Analysis of Variance 16e: Meet the Formula and Practice Problems: Two-Factor Analysis of Variance 16f: Meet the Formula and Practice Problems: One-Factor Within-Subjects Analysis of Variance 16g: Meet the Formula and Practice Problems: Correlation 16h: Meet the Formula and Practice Problems: Bivariate Regression Appendix A. Data Sets and Activities A1: Data Analysis Exercise—von Hippel, Ronay, Baker, Kjelsaas, and Murphy (2016) A2: Data Analysis Exercise—Nairne, Pandeirada, and Thompson (2008) A3: Data Analysis Project—Crammed vs. Distributed Study A4: Data Analysis Project—Teaching Techniques Study A5: Data Analysis Project—Distracted Driving Study A6: Data Analysis Project—Temperature and Air Quality Study A7: Data Analysis Project—Job Type and Satisfaction Study A8: Data Analysis Project—Attractive Face Recognition Study A9: Data Analysis Project—Discrimination in the Workplace Study Appendix B. Overview and Selection of Statistical Tests B1: Finding the Appropriate Inferential Test B2: Finding the Appropriate Inferential Test From Research Designs B3: Finding the Appropriate Inferential Test From Research Questions B4: Identifying the Design and Finding the Appropriate Inferential Test From Abstracts B5: Identifying Variables and Determining the Inferential Test From Abstracts Appendix C. Summary of Formulae References

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Book SynopsisInterpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands. This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.Table of ContentsIntroduction; Continuous predictors: Linear; Continuous predictors: Polynomials; Continuous predictors: Piecewise models; Continuous by continuous interactions; Continuous by continuous by continuous interactions; Categorical predictors; Categorical by categorical interactions; Categorical by categorical by categorical interactions; Linear by categorical interactions; Polynomial by categorical interactions; Piecewise by categorical interactions; Continuous by continuous by categorical interactions; Continuous by categorical by categorical interactions; Multilevel models; Time as a continuous predictor; Time as a categorical predictor; Nonlinear models; Complex survey data

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Book SynopsisThis unique text provides a broad introduction to qualitative analysis together with concrete demonstrations and comparisons of five major approaches. Leading scholars apply their respective analytic lenses to a narrative account and interview featuring "Teresa," a young opera singer who experienced a career-changing illness. The resulting analyses vividly exemplify what each approach looks like in action. The researchers then probe the similarities and differences among their approaches; their distinctive purposes and strengths; the role, style, and subjectivity of the individual researcher; and the scientific and ethical complexities of conducting qualitative research. Also included are the research participant's responses to each analysis of her experience. A narrative account from another research participant, "Gail," can be used by readers to practice the kinds of analysis explored in the book.Trade Review"An extraordinary achievement. This is the book I will recommend to my quantitative colleagues when they ask, 'Just what is qualitative research?' Unlike other books that give steps for doing a qualitative study, Five Ways takes the reader into the thoughts and feelings involved in conducting research. The exciting, informative interactive discussions among the researchers and the participant provide unique insights. I will use Five Ways as the basic text in my qualitative courses."--Donald E. Polkinghorne, PhD, Professor Emeritus, Department of Counseling Psychology, University of Southern California"Not only do the authors look at a common data set in five different ways, but they also reflect on how all five analyses look to each of them, and these explorations are 'looked back at' by the participant from whom the data set was derived. This book provides an engaging and intimate view of the many selves it takes to bring qualitative analyses into being and the reflexive practices that contribute to the scientific and ethical integrity of research."--Margarete Sandelowski, PhD, RN, FAAN, School of Nursing, University of North Carolina at Chapel Hill"This unique work is a wholly absorbing adventure in comparative methodology. For the student, it will serve as an effective and informative introduction to a range of central qualitative methodologies. For the seasoned scholar, it provides a wonderfully nuanced view of the complex processes of decision making in qualitative inquiry. The book challenges us to grapple with major issues: the goals of our work, its functions in the social world, and its ethical implications. This is a landmark work in the development of qualitative inquiry."--Kenneth J. Gergen, PhD, Department of Psychology, Swarthmore College"The logic of the book is transparent: it presents a narrative, multiple interpretations, and a comparison of the varied interpretations. The experience of walking through the various interpretations and then seeing how experts unpack the differences and similarities among them is remarkable. Although many books are written for introductory courses on qualitative methods, very few authors attend to how the structure of a text--not just its content--might be pedagogically significant. I applaud Wertz et al. for thinking explicitly and intentionally about how to conceptualize and organize their text in a way that facilitates learning."--Suzanne M. Wilson, PhD, Department of Teacher Education and Director, Center for the Scholarship of Teaching, Michigan State University"This text addresses one of the most frequently asked questions in qualitative analysis: what is the difference between phenomenology, grounded theory, discourse analysis, narrative research, and intuitive inquiry? The authors explain the theory that underlies each approach and illustrate its application and the resultant findings, making the book a worthy text for a qualitative methods course. As an added bonus, the authors present the participant's reaction to the results of the five different analyses and discuss the ethical implications in terms of letting the participant speak for herself, issues of confidentiality, and tensions around interpretation of data. I would definitely use this book in my advanced qualitative research course."--Donna M. Mertens, PhD, Department of Educational Foundations and Research, Gallaudet University"A powerful, richly nuanced, brilliantly innovative pedagogical intervention into the field of qualitative inquiry. This book is clearly written, grounded in case materials, and very accessible to students. The narrative is driven by the voices and insights of preeminent scholars, each an expert in one of five ways of doing qualitative analysis. This book represents the most innovative approach to date for teaching qualitative analysis. It will provide a starting place for the next generation of students who want to learn how to be well-grounded qualitative inquirers."--Norman K. Denzin, PhD, College of Communications Scholar, University of Illinois at Urbana-Champaign-Table of ContentsIntroduction I. A Story of Qualitative Research in Psychology 1. From Innovative Practices to the Call for Methodology 2. The Establishment of Methodological Traditions 3. Contemporary Movement, Methodological Pluralism, and Challenges II. Five Approaches to Qualitative Data Analysis 4. The Teresa Texts: Thick Description of Living through Misfortune 5. A Phenomenological Psychological Approach to Trauma and Resilience, Frederick J. Wertz 6. A Constructivist Grounded Theory Analysis of Losing and Regaining a Valued Self, Kathy Charmaz 7. A Discursive Analysis of Teresa’s Protocol: Enhancing Oneself, Diminishing Others, Linda M. McMullen 8. Narrative Research: Constructing, Deconstructing, and Reconstructing Story, Ruthellen Josselson 9. Intuitive Inquiry: Exploring the Mirroring Discourse of Disease, Rosemarie AndersonIII. Pluralism, Participation, and Unity in Qualitative Research 10. Comparisons through Five Lenses 11. The Participant’s Response 12. Ethics, Participant Involvement, and Analytic Methodology Appendix: Gail’s Texts

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