Psychological methodology Books

Book SynopsisWith its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website (www.guilford.com/brown3-materials) offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variaTrade Review"Brown's writing is excellent; this book does a clearer and better job of explaining CFA concepts than any other I have read. It has had a very positive impact on the quality of applied CFA studies in the social and behavioral sciences. I will continue to use the second edition in my graduate measurement theory course; it enables my students to greatly improve the quality of their dissertation research. This is the best book I've seen for providing graduate students with the skills they need to develop and evaluate measures of psychological constructs."--G. Leonard Burns, PhD, Department of Psychology, Washington State University"I am a big fan of this book. When something goes wrong in SEM, it is almost always due to a faulty measurement model, so students need to have a thorough understanding of latent trait measurement models before learning how to evaluate structural models. That is why this book is so important. My students regularly comment on how accessible the text is. I very much like the examples of study results, which students can use as templates for their own reports. The numerically worked examples throughout are extremely helpful at demystifying the process."--Lesa Hoffman, PhD, Institute for Lifespan Studies, University of Kansas"This book occupies a unique and important position in the field. It describes the use of CFA to address a wide range of important social science research questions that are too often ignored or underdeveloped in books on structural equation modeling. The text helps readers understand the nuances of CFA in a way that is deep yet incredibly accessible. I highly recommend this book to students and experienced social scientists interested in applying this powerful approach in their research."--Noel A. Card, PhD, Department of Educational Psychology, University of Connecticut"The most comprehensive reference text on CFA for experienced researchers. Other texts typically devote a chapter or two to the subject, but Brown’s coverage is wide and deep. Frankly, what gives this book value to me is that it is a reference text that can be used for instruction. Aided by clear examples, simplified tables, and helpful visual depictions, readers easily gain an understanding of how to run popular modeling software and correctly interpret the output. Perhaps one of the finest jewels in this book is the explanation of non-positive definite matrices, the bane of LISREL users. I also find the thread throughout the book on explaining equivalent models very important."--Randall MacIntosh, PhD, Professor of Sociology, California State University, Sacramento"I highly recommend this book to colleagues and students who teach and apply structural equation modeling. The book provides an invaluable resource for applied researchers concerning concepts, procedures, and problems in CFA, as well as how to interpret and report analysis results. An especially valuable feature is the many detailed examples that are worked out in detail and presented along with syntax and output from leading software packages. The Appendices at the end of several chapters expand on many technical points the reader might fail to grasp otherwise."--James G. Anderson, PhD, Department of Sociology, Purdue University "The book does an excellent job of walking through the steps in an analysis. It is wonderfully user friendly in the way it presents each step, discusses major decisions to be made, and presents code and output. Not only do I think this is the best book out there for learning CFA, but I also think it is a fantastic way to learn introductory structural equation modeling methods."--Scott J. Peters, PhD, Department of Educational Foundations, University of Wisconsin-Whitewater "A strength of this book is the style of the author's presentation. Many important concepts are explained in plain language, rather than by mathematical formula. The book reads as though you were listening to a lecture. It provides the learner with an extensive understanding of the theory and applications of CFA. I also strongly recommend this book to practitioners who are in need of a comprehensive reference for better applications of CFA."--Akihito Kamata, PhD, Department of Education Policy and Leadership and Department of Psychology, Southern Methodist University -Very helpful tables are used to summarize each step of a method or procedure….Chapter 3 is the heart of the textbook. It is a beautiful introduction to CFA….Summaries at the beginning and end of each chapter, an extensive number of substantive examples, figures and tables, appendices, software input and output files, as well as a sophisticated structure…make each chapter very easy to follow….Provides readers with clear recommendations and guidelines of how to deal with problems as well as a comprehensive overview of the most important aspects of CFA that an applied researcher should know. Given these outstanding qualities, I strongly believe that [this text] will continue to have a strong impact on applied researchers…and graduate students. The first edition has become a benchmark textbook in the field of introductory psychometrics, and the carefully revised second edition will widen its readership and make an impact very soon.--Journal of Educational and Behavioral Statistics, 01/01/2016Table of Contentsl. Introduction Uses of Confirmatory Factor Analysis Psychometric Evaluation of Test Instruments Construct Validation Method Effects Measurement Invariance Evaluation Why a Book on CFA? Coverage of the Book Other Considerations Summary 2. The Common Factor Model and Exploratory Factor Analysis Overview of the Common Factor Model Procedures of EFA Factor Extraction Factor Selection Factor Rotation Factor Scores Summary 3. Introduction to CFA Similarities and Differences of EFA and CFA Common Factor Model Standardized and Unstandardized Solutions Indicator Cross-Loadings/Model Parsimony Unique Variances Model Comparison Purposes and Advantages of CFA Parameters of a CFA Model Fu

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Book SynopsisAn authoritative handbook, this volume offers both a comprehensive review of the current science of mindfulness and a guide to its ongoing evolution. Leading scholars explore mindfulness in the context of contemporary psychological theories of attention, perceptual processing, motivation, and behavior, as well as within a rich cross-disciplinary dialogue with the contemplative traditions. After surveying basic research from neurobiological, cognitive, emotional/affective, and interpersonal perspectives, the book delves into applications of mindfulness practice in healthy and clinical populations, reviewing a growing evidence base. Examined are interventions for behavioral and emotion dysregulation disorders, depression, anxiety, and addictions, and for physical health conditions.Trade Review"Although psychologists were 2,500 years late to recognize the benefits of mindfulness, behavioral scientists and practitioners have made immense strides in understanding this important process. Drawing from work across the domains of psychology, this volume examines the psychological processes that underlie mindfulness, comprehensively reviews basic research, and describes mindfulness-based interventions for specific populations. The book makes an exceptional contribution as it summarizes the current state of knowledge, offers ideas for future research, and paves the way toward even more effective interventions."--Mark R. Leary, PhD, Department of Psychology and Neuroscience, Duke University "With the exponential growth of mindfulness science over the past 30 years, this book offers a timely and inclusive snapshot of how we now define mindfulness and how it might work, the ways it integrates with current psychological theory, and how it is being applied to help improve well-being and reduce suffering. For clinicians and researchers newly interested in mindfulness, this book will provide a thorough review. For those with more experience in this area, too, the volume will most certainly provide refreshing insights and perspectives."--Mark A. Lau, PhD, Vancouver CBT Center and Department of Psychiatry, University of British Columbia, Canada "Finally, the most comprehensive work on mindfulness! This handbook sums up the current state of the research and clinical applications and offers insightful discussions of multiple aspects of mindfulness. The chapters are written in a clear and interesting fashion by highly respected experts. This is useful reading for advanced students in psychology and cognitive sciences as well as health care professionals, and will be 'unputdownable' for anyone interested in learning more about mindfulness. I wholeheartedly recommend this excellent book."--Britta Hölzel, PhD, Harvard Medical School/Massachusetts General Hospital and Department of Neuroradiology, Technical University of Munich, Germany "The mindfulness literature is growing so fast that keeping up can seem impossible. This volume helps tremendously. Ancient Buddhist teachings and their relationship to contemporary Western scientific approaches are thoughtfully discussed. Theoretical viewpoints, measurement issues, and basic research findings on the brain, cognition, and emotion are covered in depth, as are mindfulness-based interventions for healthy individuals and those with mental and physical health problems. This is an outstanding volume from a distinguished group of contributors."--Ruth A. Baer, PhD, Department of Psychology, University of Kentucky "A welcome and needed addition to the burgeoning literature of mindfulness. Readers get a solid grasp of the historical roots and current applications of mindfulness and are introduced to psychological models--both well established and more recent--that provide a context for understanding the effects of contemplative practices on body, brain, and mind. Various levels of analysis are provided, including neurobiological, cognitive, affective and psychological perspectives. The emphasis on empirical research and reasoned argument will make this volume an invaluable text for graduate-level courses."--Tony Toneatto, PhD, Department of Psychiatry, University of Toronto, Canada -This is one of the most thorough books on mindfulness to date that I am aware of, with relevant and essential input of well-respected experts. It is a valued contribution, which summarizes not only the current state of knowledge, but provides some useful ideas for the next steps in mindfulness research.--Private Practice, 7/1/2016ƒƒ[The] Handbook of Mindfulness: Theory, Research, and Practice is an easy read that is tailored to those who are novices in exploring this timely topic. It would be most helpful to researchers who wish to have a compact volume that summarizes all aspects of the state of the art of meditation for mental health professionals….Because of the breadth examined, it would be an excellent choice for a textbook….Supervising clinicians who wish to quickly access common terms, themes, and clinical applications related to meditation as well as overviews of common mindfulness-based therapies would be satisfied. Content would be readable for trainees from the practicum to postdoctoral level of these well written and relatively brief 'meta-analyses' of sorts.--PsycCRITIQUES, 9/28/2015ƒƒThis book appears to be a major feat in the industry…seldom does one see something this complete, detailed, well balanced by the editors, informative, solid, and reliable in not pandering to the spiritual, but rather in answering the questions it set out to address: the nature of the theory, research, and practice of mindful interventions. It belongs on your shelf.--Metapsychology Online Reviews, 8/18/2015ƒƒImpressive….Highly recommended. Graduate students, researchers, professionals.--Choice Reviews, 8/1/2015Table of Contents1. Introduction: The Evolution of Mindfulness Science, Kirk Warren Brown, J. David Creswell, & Richard M. RyanI. Historical and Conceptual Overview of Mindfulness 2. Buddhist Conceptualizations of Mindfulness, Rupert Gethin 3. Developing Attention and Decreasing Affective Bias: Toward a Cross-Cultural Cognitive Science of Mindfulness, Jake H. Davis & Evan Thompson 4. Reconceptualizing Mindfulness: The Psychological Principles of Attending in Mindfulness Practice and Their Role in Well-Being, James CarmodyII. Mindfulness in the Context of Contemporary Psychological Theory 5. Mindfulness in the Context of the Attention System, Yi Yuan Tang & Michael I. Posner 6. Mindfulness in the Context of Processing Mode Theory, Edward R.Watkins 7. Being Aware and Functioning Fully: Mindfulness and Interest-Taking within Self-Determination Theory, Edward L. Deci, Richard M. Ryan, Patricia P. Schultz, & Christopher P. Niemiec 8. Mindfulness in Contextual Cognitive-Behavioral Models, Thomas G. Szabo, Douglas M. Long, Matthieu Villatte & Steven C. HayesIII. Basic Science of Mindfulness 9. From Conceptualization to Operationalization of Mindfulness, Jordan T. Quaglia, Kirk Warren Brown, Emily K. Lindsay, J. David Creswell, & Robert J. Goodman 10. The Neurobiology of Mindfulness Meditation, Fadel Zeidan 11. Cognitive Benefits of Mindfulness Meditation, Marieke K. van Vugt 12. Emotional Benefits of Mindfulness, Joanna J. Arch & Lauren N. Landy 13. The Science of Presence: A Central Mediator of the Interpersonal Benefits of Mindfulness, Suzanne C. Parker, Benjamin W. Nelson, Elissa S. Epel, Daniel J. Siegel 14. Did the Buddha Have a Self?: No-Self, Self, and Mindfulness in Buddhist Thought and Western Psychologies, Richard M. Ryan & C. Scott RigbyIV. Mindfulness Interventions for Healthy Populations 15. Mindfulness-Based Stress Reduction for Healthy Stressed Adults, Shauna L. Shapiro & Hooria Jazaieri 16. Mindfulness Training for Children and Adolescents: A State-of-the-Science Review, David S. Black 17. Mindfulness Training to Enhance Positive Functioning, Kirk Warren BrownV. Mindfulness Interventions for Clinical Populations 18. Mindfulness Interventions for Emotional Dysregulation Disorders: From Self-Control to Self-Regulation, Thomas R. Lynch, Sophie A. Lazarus, & Jennifer S. Cheavens 19. Mindfulness-Based Cognitive Therapy for Chronic Depression, Julie Anne Irving, Norman A. S.Farb, & Zindel V. Segal 20. Mindfulness in the Treatment of Anxiety, Sarah A. Hayes-Skelton & Lauren P. Wadsworth 21. A Mindfulness-Based Approach to Addiction, Sarah Bowen, Cassandra Vieten, Katie Witkiewitz, & Haley Douglas 22. Mindfulness-Based Interventions for Physical Conditions: A Selective Review, Linda E. Carlson 23. Biological Pathways Linking Mindfulness with Health, J. David Creswell

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Book SynopsisThe ongoing growth of attachment research has given rise to new perspectives on classic theoretical questions as well as fruitful new debates. This unique book identifies nine central questions facing the field and invites leading authorities to address them in 46 succinct chapters. Multiple perspectives are presented on what constitutes an attachment relationship, the best ways to measure attachment security, how internal working models operate, the importance of early attachment relationships for later behavior, challenges in cross-cultural research, how attachment-based interventions work, and more. The concluding chapter by the editors delineates points of convergence and divergence among the contributions and distills important implications for future theory and research.Trade Review"This book will prove richly rewarding to those already deeply steeped in attachment theory, research, clinical intervention, and even public policy, as well as those new to the subject. It could serve as a primary text for a graduate psychology class. The book comprises brief chapters by developmental, social, biological, and clinical psychologists who both embrace and critique attachment theory and research. It provides deep insight into such fundamental issues as conceptualization and measurement of attachment security across the life course, determinants and consequences of variation in security/insecurity and attachment state of mind, and underlying neurobiology. Classical and cutting-edge research is masterfully reported and evaluated in an effort to move the field in an interdisciplinary lifespan direction. This volume is an intellectual feast--enjoy the meal!"--Jay Belsky, PhD, Robert M. and Natalie Reid Dorn Professor, Program in Human Development, University of California, Davis "This is a volume of extraordinary importance for our knowledge about attachment relationships in human development, and for the application of that knowledge in systems across the lifespan and across societies. It could not be more timely as an incisive update on attachment research, which over the past decade has expanded and has been increasingly extended into neuroscience and education. Many fields will no doubt benefit from the rich insights provided by these chapters. I have no doubt that this landmark volume will be a standard reference for years to come."--Robert C. Pianta, PhD, Novartis US Foundation Professor of Education and Dean, School of Education and Human Development, University of Virginia "This is one of the more important books on attachment theory of the last few decades. Thompson, Simpson, and Berlin have brought together a who’s who of attachment scholars to confront nine fundamental issues. Several innovations make this a standout volume--among them, the mix of senior and emerging scholars, which leads to fresh perspectives on crucial questions, and the focused, concise chapter format. This book will serve to stimulate ideas in those familiar with the field and will be an excellent text for graduate courses on research and theory in developmental psychology."--Megan R. Gunnar, PhD, Regents Professor, Institute of Child Development, University of Minnesota "Attachment theory has grown continuously, with increasing relevance for theoretical, clinical, research, and public policy domains. Thompson, Simpson, and Berlin, together with their excellent contributors, have produced a volume of immeasurable significance. Chapters assess where the field of attachment currently stands and consider perspectives for the future. I highly recommend this comprehensive work to educators, researchers, and clinicians interested in early development."--Joy D. Osofsky, PhD, Paul J. Ramsay Endowed Chair of Psychiatry and Barbara Lemann Professor of Child Welfare, Louisiana State University Health Sciences Center "As one who has been reading and teaching and conducting research on attachment for 30-plus years, I cannot overstate this book's timeliness or value. This is exactly the book that the attachment field needs right now! And how wonderful that this theory, which has been extraordinarily generative for more than 50 years, still offers so many important questions to be explored. It was such a good idea to ask both seasoned and emerging scholars to collaborate in tackling the most fundamental questions. The editors certainly got the questions right--and the responses are penetrating and thought provoking. Every chapter is tightly focused and concise, making the book an ideal text for courses on attachment and related topics at both the graduate and advanced undergraduate levels. I am continually asked by friends and colleagues outside this area what they should read about attachment. This is the book I will be recommending!"--Cindy Hazan, PhD, Department of Psychology, Cornell University-Table of Contents1. Attachment Theory in the Twenty-First Century: Introduction to the Volume, Ross A. Thompson, Jeffry A. Simpson, & Lisa J. Berlin - TOPIC 1: Defining Attachment and Attachment Security 2. Attachment as a Relationship Construct, L. Alan Sroufe 3. What Kinds of Relationships Count as Attachment Relationships?, R. Pasco Fearon & Carlo Schuengel 4. Attachment to Child Care Providers, Lieselotte Ahnert 5. Defining Attachment Relationships and Attachment Security from a Personality–Social Perspective on Adult Attachment, Phillip R. Shaver & Mario Mikulincer 6. The Nature and Developmental Origins of Attachment Security in Adulthood, Deborah Jacobvitz & Nancy Hazen 7. Casting a Wider Net: Parents, Pair Bonds, and Other Attachment Partners in Adulthood, Ashleigh I. Aviles & Debra Zeifman - TOPIC 2: Measuring the Security of Attachment 8. Categorical Assessments of Attachment: On the Ontological Relevance of Group Membership, Howard Steele & Miriam Steele 9. Categorical or Dimensional Measures of Attachment?: Insights from Factor Analytic and Taxometric Research, K. Lee Raby, R. Chris Fraley, & Glenn I. Roisman 10. Representational Measures of Attachment: A Secure Base Script Perspective, Theodore Waters 11. Measuring the Security of Attachment in Adults: Narrative Assessments and Self-Report Questionnaires, Judith A. Crowell 12. Priming Approaches, Omri Gillath & Ting Ai - TOPIC 3: The Nature and Function of Internal Working Models 13. In the Service of Protection from Threat: Attachment and Internal Working Models, Jude Cassidy 14. From Internal Working Models to Script-Like Attachment Representations, Harriet S. Waters, Theodore E. A. Waters, & Everett Waters 15. Parental Insightfulness and Parent–Child Emotion Dialogues: Shaping Children's Internal Working Models, David Oppenheim & Nina Koren-Karie 16. Internal Working Models as Developing Representations, Ross A. Thompson 17. A Functional Account of Multiple Internal Working Models: Flexibility in Ranking, Structure and Content across Contexts and Time, Yuthika U. Girme & Nickola C. Overall - TOPIC 4: Stability and Change in the Security of Attachment 18. The Consistency of Attachment Security across Time and Relationships, R. Chris Fraley & Keely A. Dugan 19. Stability and Change in Attachment Security, Cathryn Booth-LaForce & Glenn I. Roisman 20. Beyond Stability: Toward Understanding the Development of Attachment beyond Childhood, Joseph Allen 21. Stability and Change in Adult Romantic Relationship Attachment Styles, Ramona L. Paetzold, W. Steven Rholes, & Tiffany George 22. Change in Adult Attachment Insecurity from an Interdependence Theory Perspective, Ximena B. Arriaga & Madoka Kumashiro - TOPIC 5: The Continuing Influence of Early Attachment 23. The Legacy of Early Attachments: Past, Present, Future, Glenn I. Roisman & Ashley M. Groh 24. Attachment Security and Disorganization: Etched on the Brain?, Marinus H. van IJzendoorn, Anne Tharner, & Marian J. Bakermans-Kranenburg 25. Early Attachment and Later Physical Health, Katie B. Ehrlich & Jude Cassidy 26. The Continuing Influence of Early Attachment Orientations Viewed from a Personality–Social Perspective on Adult Attachment, Mario Mikulincer & Philip R. Shaver 27. Early Attachment from the Perspective of Life History Theory, Ohad Szepsenwol & Jeffry A. Simpson - TOPIC 6: Culture and Attachment 28. Attachment Theory: Fact or Fancy?, Heidi Keller 29. Pluralities and Commonalities in Children's Relationships: Care of Efe Forager Infants as a Case Study, Gilda Morelli & Linxi Lu 30. Attachment Theory's Universality Claims: Asking Different Questions, Judi Mesman 31. Attachment in the Context of Human Adaptation, James Chisholm - TOPIC 7: Separation and Loss 32. Losing a Parent in Early Childhood: The Impact of Disrupted Attachment, Ann Chu & Alicia F. Lieberman 33. Attachment, Loss, and Grief Viewed from a Personality–Social Perspective on Adult Attachment, Philip R. Shaver & Mario Mikulincer 34. The Psychological and Biological Correlates of Separation and Loss, David A. Sbarra & Antina Manvelian 35. Breaking the Marital Ties That Bind: Divorce from a Spousal Attachment Figure, Brooke C. Feeney & Joan K. Moin 36. Normal and Pathological Mourning: Attachment Processes in the Development of Prolonged Grief, Fiona Maccallum - TOPIC 8: Attachment-Based interventions 37. Attachment-Based Interventions to Promote Secure Attachment in Children, Marian Bakermans-Kranenburg & Mirjam Oosterman 38. Mechanisms of Attachment-Based Intervention Effects on Child Outcomes, Mary Dozier & Kristin Bernard 39. Attachment-Based Intervention Processes in Disordered Parent–Child Relationships, Sheree L. Toth, Michelle E. Alto, & Jennifer Warmingham 40. Therapeutic Mechanisms in Attachment-Informed Psychotherapy with Adults, Alessandro Talia & Jeremy Holmes 41. Attachment Principles as a Guide to Therapeutic Change: The Example of Emotionally Focused Therapy, Susan M. Johnson - TOPIC 9: Attachment, Systems, and Services 42. Attachment and Child Care, Margaret Tresch Owen & Cynthia A. Frosch 43. Attachment and Early Childhood Education Systems in the United States, Bridget K. Hamre & Amanda P. Williford 44. An Attachment Theory Approach to Parental Separation, Divorce, and Child Custody, Michael E. Lamb 45. Attachment and Child Protective Systems, Jody Todd Manly, Anna Smith, Sheree L. Toth, & Dante Cicchetti 46. Attachment and Foster Care, Charles H. Zeanah & Mary Dozier 47. Attachment and Early Home Visiting: Toward a More Perfect Union, Lisa J. Berlin, Allison West, & Brenda Jones Harden 48. Concluding Commentary: Assembling the Puzzle--Interlocking Pieces, Missing Pieces, and the Emerging Picture, Ross A. Thompson, Lisa J. Berlin, & Jeffry A. Simpson Author Index Subject Index

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Book SynopsisFrom Patricia Leavy, a leader in arts-based research, this is the first comprehensive guide to what social fiction is and how to write it. In an engaging, personal tone, Leavy explores the unique contribution that creative writing--such as novels, series, and short stories--can make to addressing qualitative research questions. In-depth discussions of narrative models (such as the three-act structure) and elements (such as plot, metaphor, dialogue) are accompanied by excerpts from Leavy's published fiction, reflections on the writing process, and technical suggestions. The book offers evaluation criteria for social fiction as well as practical publishing advice. Instructive features include tip bubbles with additional writing hints, end-of-chapter Skill-Building and Rethink Your Research exercises, and an appendix with suggested readings.Trade Review"Everything you need to know to write social fiction is in this book. One of the best-written methods books I have ever read, it is accessible, clear, and detailed. The examples demonstrate the fiction concepts, and the pedagogical elements provide valuable advice and questions to think about in order to get a writing project started."--Sandra L. Faulkner, PhD, School of Media and Communication, Bowling Green State University "Leavy does a wonderful job of introducing social fiction. The flow and style are confident and easy. There are humorous sections that keep the reader engaged in a way that is often missing in dry academic research methods texts.”—Kenya E. Wolff, PhD, Department of Teacher Education, University of Mississippi "This book is excellent at explaining both the theory behind fiction as method and the practical 'how-tos' of doing it well. The exemplars from Leavy's own novels are instructive. Leavy's reflections on how she writes—how fiction is structured, what's going on behind the scenes—are so helpful. This book will be especially valuable for students coming from disciplines where fiction is not normally used, but where it could serve to make research accessible to a broader audience. I will use it in my own class."—Jessica Smartt Gullion, PhD, Department of Sociology, Texas Woman’s University "This text would be great as either a supplemental text or central text for any course exploring truth and fiction. It is especially powerful for thinking about truth in inquiry. This book resonates well with our work through the Feminist Research Collective."--Barbara Dennis, PhD, Department of Counseling and Educational Psychology, Indiana University-Table of Contents1. Writing as Inquiry 2. Historical and Contemporary Context for Social Fiction 3. The Method: How to Write Social Fiction 4. Traditional Three-Act Structures 5. Sequels: More on Traditional Three-Act Structures 6. Series and Open Form Structures 7. Alternative Structures 8. Short Stories 9. Practical Advice for Publishing and Evaluating Social Fiction Appendix. Recommended Reading References Index

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Book SynopsisWeaving together state-of-the-art research, theory, and clinical insights, this book provides a new understanding of the unconscious and its centrality in human functioning. The authors review heuristics, implicit memory, implicit learning, attribution theory, implicit motivation, automaticity, affective versus cognitive salience, embodied cognition, and clinical theories of unconscious functioning. They integrate this work with cognitive neuroscience views of the mind to create an empirically supported model of the unconscious. Arguing that widely used psychotherapies--including both psychodynamic and cognitive approaches--have not kept pace with current science, the book identifies promising directions for clinical practice.Winner--American Board and Academy of Psychoanalysis Book Prize (Theory)Trade Review“A 'must read' for anyone who wants to know how our minds and brains really work when we’re not looking. No one other than Weinberger could have pulled together this important work--no one else has spent the last 35 years working with unconscious processes both in the laboratory and the clinic, without overvaluing or devaluing either setting. Weinberger and Stoycheva synthesize the best scientific and clinical thinking about the range of unconscious processes that control our thoughts, feelings, motivation, and behavior. The authors glide effortlessly from philosophical thought on the nature of consciousness, to complex experiments in cognitive neuroscience, to provocative ideas from contemporary psychoanalysis."--Drew Westen, PhD, Department of Psychology and Department of Psychiatry and Behavioral Sciences, Emory University "What an accomplishment! Just as the scientific community approaches consensus about the ubiquity and power of unconscious processes, Weinberger and Stoycheva provide a brilliant, generous, guided tour of that landscape. The authors explore and integrate knowledge about implicit mental processes that has emerged from different intellectual traditions. This readable book belongs not only in undergraduate and graduate courses in psychology and psychiatry, but also in the curricula of all postgraduate clinical training programs."--Nancy McWilliams, PhD, ABPP, Graduate School of Applied and Professional Psychology, Rutgers, The State University of New Jersey "This impressive, authoritative book beautifully integrates the profound insights of Freudian psychology with cutting-edge research. If you have wondered about the powers and pitfalls of the human mind that lie outside of conscious, deliberate thinking, or if you are merely curious about the deep processes that produce the remarkable capacity of human thinking, this book is the place to start. It offers a thorough overview of scholarly work on the unconscious, but it goes beyond that to offer a new synthesis. This is a terrific resource for researchers, practitioners, students, and anyone else interested in the mysterious depths of the human mind."--Roy F. Baumeister, PhD, Department of Psychology, University of Queensland, Australia "Weinberger is one of the world's leading experts on the unconscious mind. He has teamed with Stoycheva to produce a contemporary review that manages to be both sweeping in its scope and illuminating in its depth. Especially valuable is their integration of psychodynamic theory and other clinical models of unconscious thought and motivation with modern cognitive psychology research on implicit memory and implicit learning. This makes the book an ideal text for cognitive science courses on conscious and unconscious human information processing, providing a more complete and historical treatment than do most contemporary texts. Advanced clinical psychology courses, as well, would profit from the coverage of therapeutic approaches and the authors' appreciation that much can be learned about the human mind and human nature from the therapy setting, in addition to rigorous laboratory research. Because the authors worked hard to describe and cover the most recent research and theoretical developments, the coverage is fresh and up to date, ensuring this book will be a trusted and useful text and resource for decades to come."--John A. Bargh, PhD, James Rowland Angell Professor of Psychology, Yale University "Weinberger and Stoycheva offer a remarkably thorough and scholarly review of the evidence on unconscious processes. Courses in academic research on affect and cognition are now a required element for PhD programs in clinical psychology, but many such courses are only peripherally relevant to clinical work. This book masterfully integrates the academic and the clinical in a way that suits the needs of both beginning graduate students and sophisticated clinicians and researchers. It is a major achievement--I learned a great deal from reading it."--Paul L. Wachtel, PhD, Distinguished Professor, Doctoral Program in Clinical Psychology, City College and the Graduate Center of the City University of New York-Table of Contents1. Introduction I. Early History of the Unconscious 2. Philosophical Precursors 3. Dynamic Psychiatry and Early Academic Psychology 4. Psychoanalysis II. Empirical Approaches to the Unconscious 5. The Beginnings of Experimental Work on Unconscious Processes 6. Unconscious Processes Move from Outcast to Mainstream 7. Empirical Tests of Unconscious Phenomena: The Effects of Subliminal Exposure 8. Attention Models Bring the Unconscious to the Mainstream 9. Unconscious Processes: From Mainstream to Central Tenet III. The Unconscious Rediscovered 10. The Normative Unconscious 11. Implicit Memory 12. Implicit Learning 13. Implicit Motivation 14. Automaticity 15. Attribution Theory 16. Affective Primacy 17. From Metaphor to Embodied Cognition IV. Computational Neuroscience and the Unconscious 18. Computational Models of the Mind 19. Massive Modularity 20. Parallel Distributed Processing 21. From Exaptation to Neural Reuse 22. A Model of the Unconscious: Theory and Implications for Psychotherapy Glossary References Index

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Book SynopsisThe second edition of this practical book equips social science researchers to apply the latest Bayesian methodologies to their data analysis problems. It includes new chapters on model uncertainty, Bayesian variable selection and sparsity, and Bayesian workflow for statistical modeling. Clearly explaining frequentist and epistemic probability and prior distributions, the second edition emphasizes use of the open-source RStan software package. The text covers Hamiltonian Monte Carlo, Bayesian linear regression and generalized linear models, model evaluation and comparison, multilevel modeling, models for continuous and categorical latent variables, missing data, and more. Concepts are fully illustrated with worked-through examples from large-scale educational and social science databases, such as the Program for International Student Assessment and the Early Childhood Longitudinal Study. Annotated RStan code appears in screened boxes; the companion website (www.guilford.coTrade Review"This very practical book is well suited to social science students because of the examples used (large-scale surveys) and the coverage of methods that social scientists often need (latent variables, variable selection, and dealing with missing data). The book also covers some topics readers may not know they need--Bayesian model averaging and workflow, for example. Illustrations use RStan, perhaps the most flexible of programs for Bayesian modeling. Full integration of RStan input and output is provided in the text."--David Rindskopf, PhD, Distinguished Professor of Educational Psychology and Psychology, The Graduate Center, The City University of New York "Kaplan's book is the perfect follow-up for those whose curiosity has been piqued about Bayesian statistics. The many code examples will give users a head start for applying Bayes' theorem to their data. I highly appreciate that the author uses open-source software for all models. The topics are introduced with a rich amount of background information, some equations (but never too many), detailed explanations, and code examples. Empirical results are used to illustrate each topic."--Rens van de Schoot, PhD, Department of Methodology and Statistics, Utrecht University, Netherlands "An excellent resource for researchers at the graduate level or above with an interest in Bayesian statistics. Readers are skillfully guided through the process of statistical reasoning from a Bayesian perspective. This book is practical and minimally technical while also introducing readers to interesting historical and philosophical issues. What makes the book especially helpful is Kaplan’s careful balance of breadth and depth of coverage of key topics. In this timely second edition, important recent advances in Bayesian statistics are distilled and disseminated for researchers in the social sciences."--Sierra A. Bainter, PhD, Department of Psychology, University of Miami "This book has all the essential components to help readers, especially quantitative researchers in social sciences, understand and conduct Bayesian modeling. The second edition includes new material on recent Markov chain Monte Carlo (MCMC) methods, such as Hamiltonian MC, in addition to a range of other updates."--Insu Paek, PhD, Senior Scientist, Human Resources Research Organization "I recommend this book for providing a careful overview of the Bayesian framework, at a level accessible to a wide audience, with examples, code, and key references. Kaplan does a great job of covering so many different aspects of Bayesian modeling in a coherent way and presenting a number of substantive methods for analyzing complex data. I liked the comparisons and analogies to the frequentist approach."--Irini Moustaki, PhD, Department of Statistics, London School of Economics and Political Science, United Kingdom-A valuable read for researchers, practitioners, teachers, and graduate students in the field of social sciences….Extremely accessible and incredibly delightful….The wide breadth of topics covered, along with the author's clear and engaging style of writing and inclusion of numerous examples, should provide an adequate foundation for any psychologist wishing to take a leap into Bayesian thinking. Furthermore, the technical details and analytic aspects provided in all chapters should equip readers with enough knowledge to embark on Bayesian analysis with their own research data. (on the first edition)--Psychometrika, 03/01/2017Table of ContentsI. Foundations 1. Probability Concepts and Bayes' Theorem 1.1 Relevant Probability Axioms 1.1.1 The Kolmogorov Axioms of Probability 1.1.2 The Rényi Axioms of Probability 1.2 Frequentist Probability 1.3 Epistemic Probability 1.3.1 Coherence and the Dutch Book 1.3.2 Calibrating Epistemic Probability Assessment 1.4 Bayes' Theorem 1.4.1 The Monty Hall Problem 1.5 Summary 2. Statistical Elements of Bayes' Theorem 2.1 Bayes' Theorem Revisited 2.2. Hierarchical Models and Pooling 2.3 The Assumption of Exchangeability 2.4 The Prior Distribution 2.4.1 Non-informative Priors 2.4.2 Jeffreys' Prior 2.4.3 Weakly Informative Priors 2.4.4 Informative Priors 2.4.5 An Aside: Cromwell's Rule 2.5 Likelihood 2.5.1 The Law of Likelihood 2.6 The Posterior Distribution 2.7 The Bayesian Central Limit Theorem and Bayesian Shrinkage 2.8 Summary 3. Common Probability Distributions and Their Priors 3.1 The Gaussian Distribution 3.1.1 Mean Unknown, Variance Known: The Gaussian Prior 3.1.2 The Uniform Distribution as a Non-informative Prior 3.1.3 Mean Known, Variance Unknown: The Inverse-Gamma Prior 3.1.4 Mean Known, Variance Unknown: The Half-Cauchy Prior 3.1.5 Jeffreys' Prior for the Gaussian Distribution 3.2 The Poisson Distribution 3.2.1 The Gamma Prior 3.2.2 Jeffreys' Prior for the Poisson Distribution 3.3 The Binomial Distribution 3.3.1 The Beta Prior 3.3.2 Jeffreys' Prior for the Binomial Distribution 3.4 The Multinomial Distribution 3.4.1 The Dirichlet Prior 3.4.2 Jeffreys' Prior for the Multinomial Distribution 3.5 The Inverse-Wishart Distribution 3.6 The LKJ Prior for Correlation Matrices 3.7 Summary 4. Obtaining and Summarizing the Posterior Distribution 4.1 Basic Ideas of Markov Chain Monte Carlo Sampling 4.2 The Random Walk Metropolis–Hastings Algorithm 4.3 The Gibbs Sampler 4.4 Hamiltonian Monte Carlo 4.4.1 No-U-Turn (NUTS) Sampler 4.5 Convergence Diagnostics 4.5.1 Trace Plots 4.5.2 Posterior Density Plots 4.5.3 Auto-Correction Plots 4.5.4 Effective Sample Size 4.5.5 Potential Scale Reduction Factor 4.5.6 Possible Error Messages When Using HMC/NUTS 4.6 Summarizing the Posterior Distribution 4.6.1 Point Estimates of the Posterior Distribution 4.6.2 Interval Summaries of the Posterior Distribution 4.7 Introduction to Stan and Example 4.8 An Alternative Algorithm: Variational Bayes 4.8.1 Evidence Lower Bound (ELBO) 4.8.2 Variational Bayes Diagnostics 4.9 Summary II. Bayesian Model Building 5. Bayesian Linear and Generalized Models 5.1 The Bayesian Linear Regression Model 5.1.1 Non-informative Priors in the Linear Regression Model 5.2 Bayesian Generalized Linear Models 5.2.1 The Link Function 5.3 Bayesian Logistic Regression 5.4 Bayesian Multinomial Regression 5.5 Bayesian Poisson Regression 5.6 Bayesian Negative Binomial Regression 5.7 Summary 6. Model Evaluation and Comparison 6.1 The Classical Approach to Hypothesis Testing and Its Limitations 6.2 Model Assessment 6.2.1 Prior Predictive Checking 6.2.2 Posterior Predictive Checking 6.3 Model Comparison 6.3.1 Bayes Factors 6.3.2 The Deviance Information Criterion (DIC) 6.3.3 Widely Applicable Information Criterion (WAIC) 6.3.4 Leave-One-Out Cross-Validation 6.3.5 A Comparison of WAIC and LOO 6.4 Summary 7. Bayesian Multilevel Modeling 7.1 Revisiting Exchangeability 7.2 Bayesian Random Effects Analysis of Variance 7.3 Bayesian Intercepts as Outcomes Model 7.4 Bayesian Intercepts and Slopes as Outcomes Model 7.5 Summary 8. Bayesian Latent Variable Modeling 8.1 Bayesian Estimation for the CFA 8.1.1 Priors for CFA Model Parameters 8.2 Bayesian Latent Class Analysis 8.2.1 The Problem of Label-Switching and a Possible Solution 8.2.2 Comparison of VB to the EM Algorithm 8.3 Summary III. Advanced Topics and Methods 9. Missing Data From a Bayesian Perspective 9.1 A Nomenclature for Missing Data 9.2 Ad Hoc Deletion Methods for Handling Missing Data 9.2.1 Listwise Deletion 9.2.2 Pairwise Deletion 9.3 Single Imputation Methods 9.3.1 Mean Imputation 9.3.2 Regression Imputation 9.3.3 Stochastic Regression Imputation 9.3.4 Hot Deck Imputation 9.3.5 Predictive Mean Matching 9.4 Bayesian Methods for Multiple Imputation 9.4.1 Data Augmentation 9.4.2 Chained Equations 9.4.3 EM Bootstrap: A Hybrid Bayesian/Frequentist Methods 9.4.4 Bayesian Bootstrap Predictive Mean Matching 9.4.5 Accounting for Imputation Model Uncertainty 9.5 Summary 10. Bayesian Variable Selection and Sparsity 10.1 Introduction 10.2 The Ridge Prior 10.3 The Lasso Prior 10.4 The Horseshoe Prior 10.5 Regularized Horseshoe Prior 10.6 Comparison of Regularization Methods 10.6.1 An Aside: The Spike-and-Slab Prior 10.7 Summary 11. Model Uncertainty 11.1 Introduction 11.2 Elements of Predictive Modeling 11.2.1 Fixing Notation and Concepts 11.2.2 Utility Functions for Evaluating Predictions 11.3 Bayesian Model Averaging 11.3.1 Statistical Specification of BMA 11.3.2 Computational Considerations 11.3.3 Markov Chain Monte Carlo Model Composition 11.3.4 Parameter and Model Priors 11.3.5 Evaluating BMA Results: Revisiting Scoring Rules 11.4 True Models, Belief Models, and M-Frameworks 11.4.1 Model Averaging in the M-Closed Framework 11.4.2 Model Averaging in the M-Complete Framework 11.4.3 Model Averaging in the M-Open Framework 11.5 Bayesian Stacking 11.5.1 Choice of Stacking Weights 11.6 Summary 12. Closing Thoughts 12.1 A Bayesian Workflow for the Social Sciences 12.2 Summarizing the Bayesian Advantage 12.2.1 Coherence 12.2.2 Conditioning on Observed Data 12.2.3 Quantifying Evidence 12.2.4 Validity 12.2.5 Flexibility in Handling Complex Data Structures 12.2.6 Formally Quantifying Uncertainty List of Abbreviations and Acronyms References Author Index Subject Index

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Book SynopsisFully updated with key advances in theory, methods, and research, the second edition of this landmark work features an expanded conceptual framework and a more global perspective on threats to human development, including climate change, war, poverty, racial injustice, and pandemics. Pioneering resilience expert Ann S. Masten illuminates the ordinary but powerful processes that allow many children exposed to trauma and adversity to survive, adapt, and even thrive. The book traces fundamental adaptive systems that have evolved and function synergistically at the neurobiological, psychological, social, community, and cultural levels. Using a range of case examples to illustrate complex concepts, Masten provides a cogent resilience framework for promoting healthy development in children at risk. New to This Edition *Advances in neurobiology, more international (including non-Western) findings and examples, new discussions of cultural identity development, up-to-date intervention research, and more. *Heightened focus on the interactions of multiple systems--including families, schools, culture, and communities--in supporting children's resilience. *Increased attention to the impact of structural inequality, poverty, and intergenerational trauma. *Coverage of rapidly emerging threats--the risks posed to children by multisystem, cascading disasters, such as the COVID-19 pandemic.

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Book SynopsisMultivariate categorical outcomes, such as Likert scale responses and disease diagnoses, require specialized structural equation modeling (SEM) software to be analyzed properly. Providing needed skills for applied researchers and graduate students, this book leads readers from regression analysis with categorical outcomes to complex SEMs with latent variables for categorical indicators. The initial section sets the stage by demonstrating regression analyses for binary, ordered, or count outcomes using R, with comparable SAS code at the companion website. Chapters then reanalyze the same data using Mplus and R lavaan to show how univariate models for categorical outcomes can be estimated and interpreted with SEM programs. Subsequently, the book turns to multivariate models, discussing path models, confirmatory factor models, and latent variable path models with categorical outcomes. Concluding chapters cover advanced SEM with categorical outcomes, including growth models, latent class models, and survival models. Worked-through examples and annotated Mplus and lavaan code are featured throughout.

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Book SynopsisThis book introduces researchers and students to the concepts and generalized linear models for analyzing quantitative random variables that have one or more bounds. Examples of bounded variables include the percentage of a population eligible to vote (bounded from 0 to 100), or reaction time in milliseconds (bounded below by 0). The human sciences deal in many variables that are bounded. Ignoring bounds can result in misestimation and improper statistical inference. Michael Smithson and Yiyun Shou′s book brings together material on the analysis of limited and bounded variables that is scattered across the literature in several disciplines, and presents it in a style that is both more accessible and up-to-date. The authors provide worked examples in each chapter using real datasets from a variety of disciplines. The software used for the examples include R, SAS, and Stata. The data, software code, and detailed explanations of the example models are available on an accompanying website.Trade ReviewThis book provides a thorough and accessible look at an important class of statistical models. It communicates intuition well and shows through numerous examples that understanding how to analyze bounded outcome variables is useful for applied researchers. -- Jeff HardenThe authors are leaders in the world-wide effort to extend and tailor the generalized linear model to variables that are bounded and not normally distributed. The discussion of models for data recorded as proportions is worth the price of admission. -- Paul JohnsonTable of Contents1. Introduction and Overview Overview of this Book The Nature of Bounds on Variables The Generalized Linear Model Examples 2. Models for Singly-Bounded Variables GLMs for singly-bounded variables Model Diagnostics Treatment of Boundary Cases 3. Models for Doubly-Bounded Variables Doubly-Bounded Variables and \Natural" Heteroskedasticity The Beta Distribution: Definition and Properties Modeling Location and Dispersion Estimation and Model Diagnostics Treatment of Cases at the Boundaries 4. Quantile Models for Bounded Variables Introduction Quantile regression Distributions for Doubly-Bounded Variables with Explicit Quantile Functions The CDF-Quantile GLM 5. Censored and Truncated Variables Types of censoring and truncation Tobit models Tobit Model Example Heteroskedastic and Non-Gaussian Tobit Models 6. Extensions and Conclusions Extensions and a General Framework Absolute Bounds and Censoring Multi-Level and Multivariate Models Bayesian Estimation and Modeling Roads Less Traveled and the State of the Art References

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Book SynopsisAlthough many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data.After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data. Each of these sections begins with an introductory chapter that provides useful background material and a broad outline to set the stage for subsequent chapters. Rather than focus on a narrowly defined topic, chapters integrate important research discussions from the statistical literature. They seamlessly blend theory with applications and include examples and case studies from various disciplines. Destined to become a landmark publication in the field, this carefully edited collection emphasizes statistical models and methods likely to endure in the future. Whether involved in the development of statistical methodology or the analysis of longitudinal data, readers will gain new perspectives on the field.Trade ReviewThe scope is remarkable, and the degree of integration and polish is admirable. The contributors include many of the most innovative researchers in the field, and happily, many of the clearest writers as well. … a lively text with clear-eyed positions and well-argued recommendations on how to analyze data of specific structures. … [material] is all accessible, well explained, and well illustrated using examples … a very good book … an excellent resource for a graduate class for statisticians or biostatisticians, and as a reference for quantitatively minded researchers.—Statistics in Medicine, 2011The volume’s editors have assembled a world-class panel of contributors; many have made seminal contributions to the field (this includes the editors themselves). Immediately apparent is the uniformity of notation and writing style not typically found in volumes of this kind. The editors clearly have taken great care to ensure a whole document rather than a disjointed patchwork typical of similar collections. Chapters reflect contributor diversity while suppressing distracting idiosyncrasies. … Experienced researchers and those new to the field will find useful material here. … several chapters provide fresh insights. For graduate students and new researchers, the book provides a useful introduction and comprehensive reference material for the topics it covers. Case studies and software enable readers to implement some methods described in the book, with supplemental datasets and programs appearing on a useful website. … A strong inaugural volume for Chapman & Hall’s new series on modern statistical methods, Longitudinal Data Analysis provides an outstanding model for future entries.—Biometrics, September 2010… Longitudinal Data Analysis is the first book to collect and sort through many of the most important developments. The authors make clear the assumptions of the statistical methods and their consequences. Coupled with an abundance of examples, the book guides the practitioner about when to apply one method as opposed to another. The book has remarkable breadth and contains material that would likely be new even to those that analyze longitudinal data on a regular basis. Longitudinal Data Analysis would be useful for applied statisticians looking to expand their analytical toolkit and statistical researchers familiar with the area but looking for a good reference. …an excellent text for a special topics course for Ph.D. students in statistics. It has a good balance of statistical theory and applications, with a large number of real data examples and case studies to illustrate how to use the methods described therein. …a well organized, excellent overview of the state of the art in modeling longitudinal data and would make a useful supplement to the library of anyone that analyzes this type of data.—Journal of the American Statistical Association, June 2010…a concise but complete encyclopedia on longitudinal data analysis. The editors have made a great effort to produce a volume providing a comprehensive and up-to-date view of the theory and application of longitudinal data analysis. … One of the strengths of the book is the organizational structure and the fact that the book has been written by well-known experts in the field. … I find this book very useful for statisticians and researchers in many fields where the interest relies on studying the change of an outcome or multiple outcomes over time. Many of the chapters include examples and case studies in different disciplines and some of this material can be found in the website of this book (http://www.biostat.harvard.edu/ fitzmaur/lda). I would like to congratulate the editors and all the contributing authors for preparing this comprehensive handbook on many interesting and complementary aspects of the theory and applications of longitudinal data analysis. This handbook will have, without any doubt, an important place on the shelf of those statisticians and applied researchers working with longitudinal data.—Journal of Applied Statistics, Vo. 36, No. 10, October 2009This is public-service broadcasting at its best. Many of the leading internationally recognized experts in the field have been assembled to write a series of expository articles on an important area of modern statistics. … Care has clearly been taken to make the book hang together—it’s not like some ‘edited tomes’ consisting of a set of papers stapled together. There is a mixture of theory and applications with real data, some of which is available on a website. In my opinion the book will be a must-have for anyone seriously involved with repeated measures or longitudinal data.—International Statistical Review, 2009Other longitudinal data books do not have the breadth of this one. … I highly recommend this book to anyone interested in learning about modern methods for longitudinal data analysis. I think it would make a particularly good book for a Ph.D.-level reading course or as a supplement to a longitudinal data textbook in a graduate-level course. I especially recommend this book to statistical researchers, as it makes a great reference book.—Journal of Biopharmaceutical Statistics, Issue 4, 2009Table of ContentsIntroduction and Historical Overview. Parametric Modeling of Longitudinal Data. Nonparametric and Semiparametric Methods for Longitudinal Data. Joint Models for Longitudinal Data. Incomplete Data. Index.

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Book SynopsisFrom distinguished scholar Donna M. Mertens, this book provides a framework for making methodological decisions and conducting research and evaluations that promote social justice. The transformative paradigm has emerged from—and guides—a broad range of social and behavioral science research projects with communities that have been pushed to the margins, such as ethnic, racial, and sexual minority group members and children and adults with disabilities. Mertens shows how to formulate research questions based on community needs, develop researcher–community partnerships grounded in trust and respect, and skillfully apply quantitative, qualitative, and mixed-methods data collection strategies. Practical aspects of analyzing and reporting results are addressed, and numerous sample studies are presented. Student- and Instructors-Friendly Features Include:*Commentary on the sample studies that explains what makes them transformative.*Explanations of key concepts related to oppression, social justice, and the role of research and evaluation.*Questions for Thought to stimulate critical self-reflection and discussion.*Advance chapter organizers and chapter summaries.Trade ReviewI've been searching for the right text for my master's-level course entitled Research in Community Settings. I've just finished reading this book, and I think it is terrific! It is just right for a course in which students will be engaging in community-university partnerships as well as learning to think critically about research.--Robb Travers, PhD, Department of Psychology, Wilfrid Laurier University, Waterloo, Ontario, CanadaAs the world becomes more interconnected and diverse, our research methods need to keep up with changes. Mertens writes beautifully about conducting research in the service of social justice, using a transformative lens and focusing clearly on each step in the process. This book illustrates why Mertens is so highly regarded for her writing that links research methods theory with practice. I highly recommend this book for researchers and graduate students across the social and human sciences.--John W. Creswell, Department of Educational Psychology, University of Nebraska-LincolnMertens focuses on using research and evaluation to transform people’s lives and communities. Including historically excluded and marginalized people in the processes of generating and using knowledge is transformative not only for research participants, but also for the researchers and evaluators who engage with them. The genius of Mertens's comprehensive approach resides in the way she makes transformative inquiry accessible and inclusive yet intellectually robust and methodologically rigorous. She invites us into the transformative process, changing the ways we both think about and conduct research and evaluation. This book is for anyone open to seriously engaging the transformative power of inclusive inquiry.--Michael Q. Patton, author of Utilization-Focused Evaluation, Fourth EditionMertens gets to the heart of how to ground research and evaluation projects in a social justice framework, in line with multiple disciplinary perspectives that embrace a transformative paradigm. This book will challenge students--including those who have not previously questioned their basic societal beliefs and assumptions--to explore diversity and oppression issues in new ways. I appreciated the inclusion of truly diverse groups, including ethnocultural minority groups and others, in the discussions of the various research and evaluation projects. The international examples and perspectives were very refreshing, too.--Gary W. Harper, Department of Psychology, DePaul University With the increase in awareness of diversity, a book like this one is long overdue. This is the first book I have read that comprehensively discusses how to approach evaluation using strategies that are culturally appropriate and inclusive of diverse communities. Mertens provides a holistic and inclusive way of thinking about research methodology. She does a wonderful job of explaining the transformative paradigm in lay language.--Katrina L. Bledsoe, Associate Project Director, Walter R. McDonald & Associates, Washington, DCThis important book assembles the complex array of procedures, perspectives, and priorities associated with transformative research and evaluation. It blends the many voices and illustrations available in the literature to assist the reader in identifying what is possible in this important new paradigm. Significant cross-cultural and international examples of studies that truly warrant the label of 'transformative' are incorporated.--Melvin E. Hall, Department of Educational Psychology, Northern Arizona University- This is the first book that specifically addresses research methodology for the transformative perspective....Although the book prioritizes an educational focus, it has relevance beyond education and scholars from management disciplines can add a practical and penetrating reading to their research toolbox....The audience encompasses novice researchers and evaluators, advanced undergraduate and beginning graduate students, more experienced teachers and evaluators....This book reminds us all that social research is embedded within a system of values and the myth of objective and value-free research should be discharged. It demonstrates how to blend science and action in an attempt to solve specific problems and promote social change. --Organizational Research Methods, 11/1/2008Table of ContentsIntroductionThe Intersection of Applied Social Research and Program EvaluationParadigmsRationale for the Transformative ParadigmBreadth of Transformative Paradigm Applicability1. Resilience, Resistance, and Complexities That Challenge In This ChapterHuman Rights AgendaThe Transformative Paradigm as a Metaphysical UmbrellaNeed for Transformative Research and EvaluationExamples of Transformative Research and EvaluationExamples of Shifting ParadigmsNeed for the Transformative Paradigm and Scholarly LiteratureNeed for the Transformative Paradigm and Public PolicyComplexities That ChallengeEthical ImpetusStriving for Improved ValiditySummary2. The Transformative Paradigm: Basic Beliefs and Commensurate Theories In This ChapterParadigms and Basic Belief SystemsThe Transformative Paradigm and Its Basic Belief SystemsTheories Commensurate with the Transformative ParadigmPolitics and PowerSummary3. Self, Partnerships, and RelationshipsIn This ChapterHuman Relations as Factors Contributing to Research Validity and RigorKnowing YourselfKnowing Yourself in Relation to the CommunityCultural CompetenceStrategies for Developing Relationships/PartnershipsTypes of Partnerships/RelationshipsChallenges in Relationships/PartnershipsRecognizing the Complexity of Culturally Competent WorkPurposes of PartnershipsExamples of Points of Interaction in the Research ProcessBuilding CapacitySummary4. Developing the Focus of Research/Evaluation StudiesIn This ChapterPurposes for the Gathering of Information at This Stage of the InquirySources That Support the Need for Research and EvaluationTheoretical FrameworksMaking Use of SourcesSummary5. A Transformative Research and Evaluation Model In This ChapterCyclical Models: Indigenous PeoplesCyclical Model: PARCyclical Models: Immigrant CommunitiesShort-Term Research and EvaluationTypes of Transformative Research and EvaluationTransformative Intervention ApproachesSummary6. Quantitative, Qualitative, and Mixed Methods In This ChapterMixed- and Multiple-Methods ApproachesCase StudiesEthnographyPhenomenology Participatory Action ResearchAppreciative InquiryExperimental and Quasi-Experimental DesignsSurvey Design and Correlational and Causal-Comparative StudiesGender Analysis: A Mixed-Methods Approach with Potential Transfer to OtherGroups That Experience DiscriminationRigor in the Process of Research and EvaluationSummary7. Participants: Identification, Sampling, Consent, and ReciprocityIn This ChapterSocial Justice: Dimensions of Diversity and Cultural CompetenceRationale for Sampling StrategiesRecruitment of ParticipantsProtection of Human Participants and Ethical Review BoardsSummary8. Data-Collection Methods, Instruments, and StrategiesIn This ChapterReliability and Validity/Dependability and CredibilityLanguage as a Critical IssuePlanning Data-Collection StrategiesSpecific Data-Collection StrategiesSummary9. Data Analysis and InterpretationIn This ChapterTransformative Theories as Guides to Data Analysis and InterpretationInvolving the Community in Analysis and In

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Book SynopsisMaximum Likelihood Estimation with Stata, Fifth Edition is the essential reference and guide for researchers in all disciplines who wish to write maximum likelihood (ML) estimators in Stata. Beyond providing comprehensive coverage of Stata’s commands for writing ML estimators, the book presents an overview of the underpinnings of maximum likelihood and how to think about ML estimation.The fifth edition includes a new second chapter that demonstrates the easy-to-use mlexp command. This command allows you to directly specify a likelihood function and perform estimation without any programming.The core of the book focuses on Stata's ml command. It shows you how to take full advantage of ml’s noteworthy features: Linear constraints Four optimization algorithms (Newton–Raphson, DFP, BFGS, and BHHH) Observed information matrix (OIM) variance estimator Outer product of gradients (OPG) variance estimator Huber/White/sandwich robust variance estimator Cluster–robust variance estimator Complete and automatic support for survey data analysis Direct support of evaluator functions written in Mata When appropriate options are used, many of these features are provided automatically by ml and require no special programming or intervention by the researcher writing the estimator.In later chapters, you will learn how to take advantage of Mata, Stata's matrix programming language. For ease of programming and potential speed improvements, you can write your likelihood-evaluator program in Mata and continue to use ml to control the maximization process. A new chapter in the fifth edition shows how you can use the moptimize() suite of Mata functions if you want to implement your maximum likelihood estimator entirely within Mata.In the final chapter, the authors illustrate the major steps required to get from log-likelihood function to fully operational estimation command. This is done using several different models: logit and probit, linear regression, Weibull regression, the Cox proportional hazards model, random-effects regression, and seemingly unrelated regression. This edition adds a new example of a bivariate Poisson model, a model that is not available otherwise in Stata.The authors provide extensive advice for developing your own estimation commands. With a little care and the help of this book, users will be able to write their own estimation commands---commands that look and behave just like the official estimation commands in Stata.Whether you want to fit a special ML estimator for your own research or wish to write a general-purpose ML estimator for others to use, you need this book.Table of ContentsTheory and practice The likelihood-maximization problem Likelihood theory The maximization problem Estimation with mlexp Syntax Normal linear regression Initial values Restricted parameters Robust standard errors The probit model Specifying derivatives Additional estimation features Wrapping up Introduction to ml The probit mode Normal linear regression Robust standard errors Weighted estimation Other features of method-gf0 evaluators Limitations Overview of ml The terminology of ml Equations in ml Likelihood-evaluator methods Tools for the ml programmer Common ml options Maximizing your own likelihood functions Appendix: More about scalar parameters Method lf The linear-form restrictions Examples The importance of generating temporary variables as doubles Problems you can safely ignore Nonlinear specifications The advantages of lf in terms of execution speed Methods lf0, lf1, and lf2 Comparing these methods Outline of evaluators of methods lf0, lf1, and lf2 Summary of methods lf0, lf1, and lf2 Examples Methods d0, d1, and d2 Comparing these methods Outline of method d0, d1, and d2 evaluators Summary of methods d0, d1, and d2 Panel-data likelihoods Other models that do not meet the linear-form restrictions Debugging likelihood evaluators ml check Using the debug methods ml trace Setting initial values ml search ml plot ml init Interactive maximization The iteration log Pressing the Break key Maximizing difficult likelihood functions Final results Graphing convergence Redisplaying output Writing do-files to maximize likelihoods The structure of a do-file Putting the do-file into production Writing ado-files to maximize likelihoods Writing estimation commands The standard estimation-command outline Outline for estimation commands using ml Using ml in noninteractive mode Advice Writing ado-files for survey data analysis Program properties Writing your own predict command Mata-based likelihood evaluators Introductory examples Evaluator function prototypes Utilities Random-effects linear regression Ado-file considerations Mata’s moptimize() function Introductory examples Restricting the estimation sample Estimation preliminaries Estimation Results Estimation commands Regression redux Other examples The logit model The probit model Normal linear regression The Weibull model The Cox proportional hazards model The random-effects regression model The seemingly unrelated regression model A bivariate Poisson regression model Epilogue Syntax of mlexp Syntax of ml Syntax of moptimize() Likelihood-evaluator checklists Method lf Method d0 Method d1 Method d2 Method lf0 Method lf1 Method lf2 Listing of estimation commands The logit model The probit model The normal model The Weibull model The Cox proportional hazards model The random-effects regression model The seemingly unrelated regression model A bivariate Poisson regression model References

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Book SynopsisResearch on Altruism and Love is a compendium of annotated bibliographies reviewing literature and research studies on the nature of love. An essay introduces each of the annotated bibliographies.A variety of literature either directly related to science-and-love issues or supporting literature for those issues is covered in the Religious Love Interfaces with Science section. This annotated bibliography is unique in that it approaches the field from a decidedly religious perspective. It includes classical expositions of love that continue to influence contemporary scholars, including Platos' work on eros, the work and words of Jesus, Aristotle, Augustine of Hippo, Martin Luther, Kierkegaard, and Ghandi, among others. The contemporary discussion includes Anders Nygren's theological arguments in his classic, Agape and Eros; Pitirim Sorokin; and others. An issue that often emerges in this literature is the question of the nature and definition of love.A second annotated bibliography features current empirical research in the field of Personality and Altruism, with a focus on social psychology. Among the topics covered are the altruistic personality, altruistic behavior, empathy, helping behavior, social responsibility, and volunteerism. Methodologies are diverse, and studies include experiments, local and national surveys, naturalistic observation, and combinations of these.The Evolutionary Biology annotated bibliography covers the most significant works on altruism and love in the field of biology and evolutionary psychology.The fourth and final annotated bibliography in this volume is entitled Sociology of Faith-Based Volunteerism. Here the focus is on literature on the interface of helping behavior and religious organizations, as well as major pieces on voluntary associations.

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Book SynopsisIn this book the author's theoretical framework builds on linguistic and psychological research, arguing that similar image-schematic notions should be grouped together into interconnected family hierarchies, with complexity increasing with regard to the addition of spatial and conceptual primitives. She introduces an image schema logic as a language to model image schemas, and she shows how the semantic content of image schemas can be used to improve computational concept invention. The book will be of value to researchers in artificial intelligence, cognitive science, psychology, and creativity.Table of ContentsCreating Concepts: Considerations from Psychology and Artificial Intelligence.- Image Schemas: Spatiotemporal Relationships Used as Conceptual Building Blocks.- Formal Structure: Image Schemas as Families of Theories.- Introducing ISLFOL: A Logical Language for Image Schemas.- Modelling Conceptualisations: Combining Image Schemas to Model Event Conceptualisations.- Generating Concepts: How Image Schemas Can Help Guide Computational.- Conceptual Blending.- Defining Concepts: Experiment on the Role of Image Schemas in Object Conceptualisation.- Identifying Image Schemas: Experiment Towards Automatic Image Schema Extraction.- Discussion and Conclusions.

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Book SynopsisThe brief, practical texts in the Essentials of Qualitative Methods series introduce social science and psychology researchers to key approaches toqualitative methods, offering exciting opportunities to gather in-depth qualitative data and to develop rich and useful findings. In this book, Gareth Terry and Nikki Hayfield introduce readers to reflexive thematic analysis, a method of analyzing interview and focus group transcripts, qualitative survey responses, and other qualitative data. Central to this method is the recognition that we are all situated in a particular context, and that we see and speak from that position.This leads researchers to produce knowledge that represents situated truths, providinginsights intopeople''s perspectives on a given topic.About the Essentials of Qualitative Methods book series: Even for experienced researchers, selecting and correctly applying the right method can be challenging. In this groundbreaking series, leading experts in qualitative methods provide clear, crisp, and comprehensive descriptions of their approach, including its methodological integrity, and its benefits and limitations. Each book includes numerous examples to enable readers to quickly and thoroughly grasp how to leverage these valuable methods.Trade ReviewThis is a clear and accessible guide to thematic analysis that will greatly appeal to students and researchers who are developing their analytic practice. The authors walk the reader through the steps of analysis, which are illustrated with clear commentary and helpful examples. -- Abigail Locke, PhD, Professor of Critical Social & Health Psychology, Keele University, Keele, UKTerry and Hayfield demystify reflexive thematic analysis with analogies from everyday life and offer hacks for fixing common mistakes. This book is a must-read for students and researchers conducting thematic analysis. -- Adam Jowett, PhD, School of Psychological, Social & Behavioural Sciences, Coventry University, Coventry, UK

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Book SynopsisA step-by-step guide to a research method that investigates how people make sense of their lived experience in the context of their personal and social worlds.Trade ReviewThis is an excellent guide to the theory and practice of interpretative phenomenological analysis; it is well written, carefully organized, engaging, and accessible. The authors have a remarkable knack for anticipating and effectively answering the questions that are typically raised by novice researchers as well as guiding them through the intricacies of qualitative research. -- Steen Halling, PhD, Professor Emeritus, Department of Psychology, Seattle University, Seattle, WA, United StatesFrom setting the background context to interpretative phenomenological analysis (IPA) through to offering exemplar studies, this book gives a thorough introduction to the steps a novice researcher will need to follow to conduct their first study using this method. The clear and concise summary also serves as an excellent refresher for anyone returning to IPA as an analytic method after some time away. An excellent addition to qualitative methodology bookshelves. -- Jane Montague, PhD, School of Psychology, University of Derby, Derby, United KingdomTable of ContentsSeries Foreword—Clara E. Hill and Sarah Knox Chapter 1: What Is Interpretative Phenomenological Analysis? A Note on Terminology Theoretical Underpinnings of IPA Chapter 2: Designing an IPA Study Choosing a Topic and a Research Question Determining What Type of Data to Collect Sampling and Recruiting Participants Practical and Ethical Considerations Chapter 3: Collecting Data Rationale for an Interview Guide How to Design an Interview Guide Conducting the Interview Transcription Chapter 4: Analyzing the Data: Starting With the First Case Step 1. Reading and Exploratory Notes Step 2. Formulating Experiential Statements Step 3. Finding Connections and Clustering Experiential Statements Step 4. Compiling the Table of Person Experiential Themes Some More Thoughts on Clustering and Compiling One Case or More Than One Case? Chapter 5: Cross-Case Analysis Chapter 6: Writing Up the Study Results Section Other Sections of an IPA Manuscript Chapter 7: Variations on the Method and More Complex Designs Chapter 8: Methodological Integrity Chapter 9: Summary and Conclusions Deciding Whether IPA Is the Right Methodology for You Concluding Words Appendix: Exemplar Studies References Index About the Authors About the Series Editors

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Book Synopsis

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Book SynopsisKeeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world. The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual undeTrade ReviewIn statistics, R is the way of the future. The big boys and girls have known this for some time: There are now millions of R users in academia and industry. R is free (as in no cost) and free (as in speech). Andy, Jeremy, and Zoe′s book now makes R accessible to the little boys and girls like me and my students. Soon all classes in statistics will be taught in R. I have been teaching R to psychologists for several years and so I have been waiting for this book for some time. The book is excellent, and it is now the course text for all my statistics classes. I′m pretty sure the book provides all you need to go from statistical novice to working researcher. Take, for example, the chapter on t-tests. The chapter explains how to compare the means of two groups from scratch. It explains the logic behind the tests, it explains how to do the tests in R with a complete worked example, which papers to read in the unlikely event you do need to go further, and it explains what you need to write in your practical report or paper. But it also goes further, and explains how t-tests and regression are related---and are really the same thing---as part of the general linear model. So this book offers not just the step-by-step guidance needed to complete a particular test, but it also offers the chance to reach the zen state of total statistical understanding. Prof. Neil StewartWarwick University Field′s Discovering Statistics is popular with students for making a sometimes deemed inaccessible topic accessible, in a fun way. In Discovering Statistics Using R, the authors have managed to do this using a statistics package that is known to be powerful, but sometimes deemed just as inaccessible to the uninitiated, all the while staying true to Field′s off-kilter approach. Dr Marcel van Egmond University of Amsterdam Probably the wittiest and most amusing of the lot (no, really), this book takes yet another approach: it is 958 pages of R-based stats wisdom (plus online accoutrements)... A thoroughly engaging, expansive, thoughtful and complete guide to modern statistics. Self-deprecating stories lighten the tone, and the undergrad-orientated ′stupid faces′ (Brian Haemorrhage, Jane Superbrain, Oliver Twisted, etc.) soon stop feeling like a gimmick, and help to break up the text with useful snippets of stats wisdom. It is very mch a student textbook but it is brilliant... Field et al. is the complete package.David M. Shuker AnimJournal of Animal Behaviour "This work should be in the library of every institution where statistics is taught. It contains much more content than what is required for a beginning or advanced undergraduate course, but instructors for such courses would do well to consider this book; it is priced comparably to books which contain only basic material, and students who are fascinated by the subject may find the additional material a real bonus. The book would also be very good for self-study. Overall, an excellent resource." -- R. Bharath * Choice *The main strength of this book is that it presents a lot of information in an accessible, engaging and irreverent way. The style is informal with interesting excursions into the history of statistics and psychology. There is reference to research papers which illustrate the methods explained, and are also very entertaining. The authors manage to pull off the Herculean task of teaching statistics through the medium of R... All in all, an invaluable resource. -- Paul WebbTable of ContentsWhy Is My Evil Lecturer Forcing Me to Learn Statistics? What will this chapter tell me? What the hell am I doing here? I don′t belong here Initial observation: finding something that needs explaining Generating theories and testing them Data collection 1: what to measure Data collection 2: how to measure Analysing data What have I discovered about statistics? Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Everything You Ever Wanted to Know About Statistics (Well, Sort of) What will this chapter tell me? Building statistical models Populations and samples Simple statistical models Going beyond the data Using statistical models to test research questions What have I discovered about statistics? Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research The R Environment What will this chapter tell me? Before you start Getting started Using R Getting data into R Entering data with R Commander Using other software to enter and edit data Saving Data Manipulating Data What have I discovered about statistics? R Packages Used in This Chapter R Functions Used in This Chapter Key terms that I′ve discovered Smart Alex′s Tasks Further reading Exploring Data with Graphs What will this chapter tell me? The art of presenting data Packages used in this chapter Introducing ggplot2 Graphing relationships: the scatterplot Histograms: a good way to spot obvious problems Boxplots (box-whisker diagrams) Density plots Graphing means Themes and options What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Exploring Assumptions What will this chapter tell me? What are assumptions? Assumptions of parametric data Packages used in this chapter The assumption of normality Testing whether a distribution is normal Testing for homogeneity of variance Correcting problems in the data What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Correlation What will this chapter tell me? Looking at relationships How do we measure relationships? Data entry for correlation analysis Bivariate correlation Partial correlation Comparing correlations Calculating the effect size How to report correlation coefficents What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Regression What will this chapter tell me? An Introduction to regression Packages used in this chapter General procedure for regression in R Interpreting a simple regression Multiple regression: the basics How accurate is my regression model? How to do multiple regression using R Commander and R Testing the accuracy of your regression model Robust regression: bootstrapping How to report multiple regression Categorical predictors and multiple regression What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Logistic Regression What will this chapter tell me? Background to logistic regression What are the principles behind logistic regression? Assumptions and things that can go wrong Packages used in this chapter Binary logistic regression: an example that will make you feel eel How to report logistic regression Testing assumptions: another example Predicting several categories: multinomial logistic regression What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Comparing Two Means What will this chapter tell me? Packages used in this chapter Looking at differences The t-test The independent t-test The dependent t-test Between groups or repeated measures? What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Comparing Several Means: ANOVA (GLM 1) What will this chapter tell me? The theory behind ANOVA Assumptions of ANOVA Planned contrasts Post hoc procedures One-way ANOVA using R Calculating the effect size Reporting results from one-way independent ANOVA What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Analysis of Covariance, ANCOVA (GLM 2) What will this chapter tell me? What is ANCOVA? Assumptions and issues in ANCOVA ANCOVA using R Robust ANCOVA Calculating the effect size Reporting results What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Factorial ANOVA (GLM 3) What will this chapter tell me? Theory of factorial ANOVA (independant design) Factorial ANOVA as regression Two-Way ANOVA: Behind the scenes Factorial ANOVA using R Interpreting interaction graphs Robust factorial ANOVA Calculating effect sizes Reporting the results of two-way ANOVA What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Repeated-Measures Designs (GLM 4) What will this chapter tell me? Introduction to repeated-measures designs Theory of one-way repeated-measures ANOVA One-way repeated measures designs using R Effect sizes for repeated measures designs Reporting one-way repeated measures designs Factorisal repeated measures designs Effect Sizes for factorial repeated measures designs Reporting the results from factorial repeated measures designs What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Mixed Designs (GLM 5) What will this chapter tell me? Mixed designs What do men and women look for in a partner? Entering and exploring your data Mixed ANOVA Mixed designs as a GLM Calculating effect sizes Reporting the results of mixed ANOVA Robust analysis for mixed designs What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Non-Parametric Tests What will this chapter tell me? When to use non-parametric tests Packages used in this chapter Comparing two independent conditions: the Wilcoxon rank-sum test Comparing two related conditions: the Wilcoxon signed-rank test Differences between several independent groups: the Kruskal-Wallis test Differences between several related groups: Friedman′s ANOVA What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Multivariate Analysis of Variance (MANOVA) What will this chapter tell me? When to use MANOVA Introduction: similarities and differences to ANOVA Theory of MANOVA Practical issues when conducting MANOVA MANOVA using R Robust MANOVA Reporting results from MANOVA Following up MANOVA with discriminant analysis Reporting results from discriminant analysis Some final remarks What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Exploratory Factor Analysis What will this chapter tell me? When to use factor analysis Factors Research example Running the analysis with R Commander Running the analysis with R Factor scores How to report factor analysis Reliability analysis Reporting reliability analysis What have I discovered about statistics? R Packages Used in This Chapter R Functions Used in This Chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Categorical Data What will this chapter tell me? Packages used in this chapter Analysing categorical data Theory of Analysing Categorical Data Assumptions of the chi-square test Doing the chi-square test using R Several categorical variables: loglinear analysis Assumptions in loglinear analysis Loglinear analysis using R Following up loglinear analysis Effect sizes in loglinear analysis Reporting the results of loglinear analysis What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Multilevel Linear Models What will this chapter tell me? Hierarchical data Theory of multilevel linear models The multilevel model Some practical issues Multilevel modelling on R Growth models How to report a multilevel model What have I discovered about statistics? R packages used in this chapter R functions used in this chapter Key terms that I′ve discovered Smart Alex′s tasks Further reading Interesting real research Epilogue: Life After Discovering Statistics Troubleshooting R Glossary Appendix Table of the standard normal distribution Critical Values of the t-Distribution Critical Values of the F-Distribution Critical Values of the chi-square Distribution References

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Book SynopsisDieses Lehrbuch führt in die theoretischen Grundlagen und praktischen Vorgehensweisen der Untersuchung von "narrativer Identität" anhand von autobiografischen Erzählinterviews ein.Table of ContentsSprache als Wirklichkeitskonstruktion - Autobiografisches Erzählen - Die 'narrative Identität' - Das Erzählinterview als empirischer Zugang - Grundlagen der Interpretation - Grundlagen des textanalytischen Arbeitens - Fokussierung der Interpretation - Praxis der Textanalyse - Strukturelle Aspekte der autobiographischen Gesamterzählung - Feinanalyse - Übergreifende Darstellungs- und Kommunikationsstrategien der Erzähler - Die praktischen Arbeitsschritte der Textanalyse - Planung und Durchführung des narrativen Interviews - Die Überführung des Interviews in den Text - Textaufbereitung - Sequenzanalyse - Fallübergreifende Techniken - Darstellung der Forschungsergebnisse

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Book SynopsisMost of us walk through each day expecting few surprises. If we want to better ourselves or our lives, we map out a path of gradual change, perhaps in counseling or psychotherapy. Psychologists William Miller and Janet C'de Baca were longtime scholars and teachers of traditional approaches to self-improvement when they became intrigued by a different sort of change that was sometimes experienced by people they encountered--something often described as a bolt from the blue or seeing the light. And when they placed a request in a local newspaper for people's stories of unexpected personal transformation, the deluge of responses was astounding. These compelling stories of epiphanies and sudden insights inspired Miller and C'de Baca to examine the experience of quantum change through the lens of scientific psychology. Where does quantum change come from? Why do some of us experience it, and what kind of people do we become as a result? The answers that this book arrives at yield remarkable insights into how human beings achieve lasting change--sometimes even in spite of ourselves. Trade ReviewBill Miller and Janet C'de Baca have written a wonderful book. Not since William James's Varieties of Religious Experience has there been such a psychologically penetrating book on spiritual experience. --George E. Vaillant, MD, Harvard Medical School Although many people spend years struggling to fix personal problems, some people undergo sudden, dramatic, and nearly instantaneous change. This book tells their stories and identifies the core features of these transformational changes. The idea of quantum change is arguably among the most exciting in psychology, since it challenges both common sense and clinical lore. This book will appeal to anyone interested in psychological change, transformation, or the human condition. In other words, this book is for everyone. --Todd F. Heatherton, PhD, Associate Professor, Department of Psychological and Brain Sciences, Dartmouth CollegeReading Quantum Change is a mystical experience of its own. This is an exceptionally well written book that I found inspirational, enlightening, and a 'must read.' After reading this book, don't be surprised if you think about change in a new way. --Monty Roberts, author of the New York Times best seller, The Man Who Listens to Horses -Table of ContentsI. The Context1. Something Old, Something New2. The Landscape of Quantum Change3. BeforeII. Insights4. The Insightful Type of Quantum Change5. Boom6. Taking the AA Train7. A Mirror and Two Roses8. Awakening9. RipplesIII. Epiphanies10. The Mystical Type of Quantum Change11. The Reluctant Mystic12. Something Like a Star13. A Voice in the Fireplace14. At Pecos15. TrampolineIV. Reflections16. After17. Are Quantum Changes Always Positive?18. What Happened?19. Messages to HumankindEpilogueAn InvitationAppendix. Values: What Matters Most to You?Notes

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Book SynopsisWrite It Up is for anyone writing an empirical article in APA Style amp reg , from beginners facing their first article to old dogs looking for new writing strategies. Your academic writing will be more influential if you approach it reflectively and strategically. Based on his experience as an author, journal editor, and peer reviewer, Paul J. Silvia offers sage and witty advice on problems like picking journals cultivating the right tone and style for your article managing collaborative projects and coauthors crafting effective Introduction, Method, Results, and Discussion sections and submitting and resubmitting papers to journals. Write It Up features: amp bull readable and amusing, the book shows, step-by-step, how to plan and organize your academic writing and amp bull uses real-world examples to illustrate how to improve writing style and write better articles.Trade ReviewIn the world of academia, once in a while, we are privileged to read a book that is both educational and entertaining … Silvia's Write It Up is a book that should be on the shelves of every aspiring writer, academic and researcher. * Child Adolescent Social Work Journal *The discussion is so well rounded, topical, and useful for one's career, this book should be required supplemental reading in graduate school for courses such as research methods. * Doody's Review Service *Its reasonable price, logical organization, and practical suggestions make it a reference that anyone who wants to have a better understanding of how to get articles published in their journal of choice might benefit from owning. * PsycCRITIQUES *From practical advice on grammar to tips, tricks, and common pitfalls when co-authoring papers, Write it Up is an absolute must-have for any scientific or academic seeking to build their reputation through published journal articles. * Midwest Book Review *Table of Contents Preface Introduction I. Planning and Prepping How and When to Pick a Journal Tone and Style Writing With Others: Tips for Coauthored Papers II. Writing the Article Writing the Introduction Writing the Method Writing the Results Writing the Discussion Arcana and Miscellany: From Titles to Footnotes III. Publishing Your Writing Dealing With Journals: Submitting, Resubmitting, and Reviewing One of Many: Building a Body of Work References Index About the Author

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Book SynopsisTreating borderline patients is one of the most challenging areas in psychotherapy because of the patient's extreme emotional expressions,and the strain it places on the therapist. Transference-Focused Therapy (TFP) is psychodynamic treatment designed especially for borderline patients. This book provides a comprehensive introduction to TFP.Trade ReviewA Primer of Transference-Focused Psychotherapy for the Borderline Patient provides an excellent introduction and resource guide for object-relations therapy for these [borderline] patients. This is an excellent introductory and reference source forobject-relations therapy with borderline patients. It is user-friendly and practical in its discussions of theory, technique, and long-term considerations for ethical and therapeutic pitfalls. An abundance of resource and bibliographic references are provided to direct the reader to more in-depth discussions of the key topics. The text provides a road map for the budding therapist when encountering splitting, therapeutic boundaries, and threats to the treatment contract. Excellent examples are provided to illustrate the identification of negative object dyads and ways they are manifest in transference material.. * PsycCRITIQUES *In this remarkable volume, Yeomans, Clarkin, and Kernberg have accomplished the impossible by combining a highly sophisticated theory of psychopathology and technique with a practical handbook for the treatment of borderline patients. The reader will find here a concise review of a psychoanalytic approach to understanding borderline personality organization. The clinician will also find a detailed step-by-step guide to the complex process of turning the emotionally intense and often chaotic interactions generated by these patients into useful psychotherapeutic dialogue. While this book presents itself as A Primer of Transference-Focused Psychotherapy for the Borderline Patient, it has much to offer psychodynamic psychotherapists at all levels of experience in their treatment of patients at all levels of personality organization. -- Elizabeth L. Auchincloss, M.D., Weill Medical College of Cornell UniversityYeomans, Clarkin, and Kernberg's A Primer of Transference-Focused Psychotherapy for the Borderline Patient stands out like a beacon to the rest of the psychodynamic community. In an era of empirically supported therapies, the work of the Cornell group has shown that it can be done, that it can be done superbly, and that it can be done without violating a single one of our cherished ideals as psychoanalytic clinicians. This is an excellent and immensely helpful introduction to the most successful program of intervention research on psychodynamic psychotherapy anywhere. It is a must-have. -- Peter Fonagy, University College, LondonA Primer of Transference-Focused Psychotherapy for the Borderline Patient provides an excellent introduction and resource guide for object-relations therapy for these [borderline] patients. This is an excellent introductory and reference source for object-relations therapy with borderline patients. It is user-friendly and practical in its discussions of theory, technique, and long-term considerations for ethical and therapeutic pitfalls. An abundance of resource and bibliographic references are provided to direct the reader to more in-depth discussions of the key topics. The text provides a road map for the budding therapist when encountering splitting, therapeutic boundaries, and threats to the treatment contract. Excellent examples are provided to illustrate the identification of negative object dyads and ways they are manifest in transference material. * PsycCRITIQUES *

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Book SynopsisThis book explores how an object relations-integrative perspective may combine in-depth psychodynamic principles and theories with the flexibility afforded by an integrative framework. Object relations theory is rooted in a psychoanalytic tradition which views individuals essentially social and holds that their need for others is primary. Integrative psychotherapy attempts to combine the theories and/or techniques of two or more therapeutic approaches. This volume is useful for graduates, undergraduates and trainee psychotherapists as well as social workers, psychologists, psychotherapists and counsellors who are interested in broadening their understanding of different therapeutic approaches and intefrative endeavours. The contributors consist of an international group of practitioners and theoreticians who draw on the knowlege of object realtions and other therapeutic orientations as well as innovations in the integrative movement. Some of te contributors grapple directly with integrative questions, while others examine ways of working with specific client groups or methods, where integrative ideas enrich their work.Table of ContentsAcknowledgements. List of contributors. Chapter 1 Tradition and innovation in theory and practice: an orientation, Inger Safvestad Nolan and Patrick Nolan. Chapter 2 Object relations as a context for an integrative approach to psychotherapy, Patrick Nolan. Chapter 3 Integrative and object relations focused approaches to psychotherapy: theoretical concerns and outcome research, George Stricker and Jane Gooen-Piels. Chapter 4 An object relations based integrative psychotherapy: the use of conceptuala analysis in understanding change, Hilde Rapp. Chapter 5 Integration of theory: methodolical issues, Mikael Leiman and William B. Stiles. Chapter 6 Developmetnal theories in the process of change, Margareta Broden. Chapter 7 Integrating object relations narratives in analytic work with children and adolescents, Paul Sepping. Chapter 8 The weave of object relations and familty systems thinking: working therapeutically with families and couples in a community alcohol service, Arlene Vetere and Mavis Henley. Chapter 9 Cognitive Analytic Therapy: a Vygotskian development of object relations theory, Anthony Ryle and Fierman Bennink-Bolt. Chapter 10 Sexual abuse, post-traumatic stress and object relations: an integrative way of working, Deirdre Mannion. Chapter 11 An integrative approach to body oriented psychotherapy, Lennart Ramberg and Bjorn Wrangsjo. Chapter 12 Supervision from an object relations and integrative perspective: a learning from experience, Gertrud Mander. Chapter 13 The strengths and limitations of a psychodynamic perspective in organizational consultancy, Eric Miller. Chapter 14 Tribal processes in psychotherapy: the stand off between psychoanalytic and systemic schools, Sebastian Kraemer. Index.

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Book Synopsis Dominic Upton, University of Worcester Holly Andrews, University of Worcester Catherine Steele, University of Worcester Table of ContentsAcknowledgementsIntroductionGuided tourGuided tour of the companion website Chapter 1 An introduction to statistics for psychologyChapter 2 Basic conceptsChapter 3 Describing the data: distribution, averages and varianceChapter 4 Chi-square analysisChapter 5 Correlation analysisChapter 6 T-testsChapter 7 Comparing data: more than two groupsChapter 8 Multiple regression analysisChapter 9 Presenting the data: tables, figures and graphsChapter 10 Interpreting data: drawing conclusions And finally, before the exam . . . Glossary of termsReferencesIndex

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Book Synopsis*What do advanced statistical techniques do?*When is it appropriate to use them?*How are they carried out and reported?There are a variety of statistical techniques used to analyse quantitative data that masters students, advanced undergraduates and researchers in the social sciences are expected to be able to understand and undertake. This book explains these techniques, when it is appropriate to use them, how to carry them out and how to write up the results. Most books which describe these techniques do so at too advanced or technical a level to be readily understood by many students who need to use them. In contrast the following features characterise this book:- concise and accessible introduction to calculating and interpreting advanced statistical techniques- use of a small data set of simple numbers specifically designed to illustrate the nature and manual calculation of the most important statistics in each technique- succinct illustration of wrTable of ContentsSeries editor’s foreword Preface 1 IntroductionPART 1Grouping quantitative variables together2 Exploratory factor analysis3 Confirmatory factor analysis4 Cluster analysisPART 2Explaining the variance of a quantitative variable5 Stepwise multiple regression6 Hierarchical multiple regressionPART 3Sequencing the relationships between three or more quantitativevariables7 Path analysis assuming no measurement error8 Path analysis accounting for measurement error PART 4Explaining the probability of a dichotomous variable 9 Binary logistic regression PART 5Testing differences between group means 10 An introduction to analysis of variance and covariance 11 Unrelated one-way analysis of covariance 12 Unrelated two-way analysis of variance PART 6Discriminating between groups 13 Discriminant analysisPART 7Analysing frequency tables with three or more qualitative variables 14 Log-linear analysis Glossary References Index

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Book Synopsis"Roberts is certainly successful in conveying a sense of the rich diversity of biographical research. This is a book based upon a formidably wide-ranging bibliography together with his own, by no means insignificant, contributions to the fieldâ[the]âreader will be left in no doubt as to the central importance of biographical research and of its legitimate position within the social sciences" - David Morgan, Emeritus Professor of Sociology, Manchester University (former President, British Sociological Association), Auto/Biography, a BSA Study Group journal, 2002."Brian Robertsâ book is a highly accessible introduction to biographical methodâThe author deftly and confidently addresses the available work in a variety of disciplines ranging from education through oral history, feminism to memoryâ I warmly recommend this book to any historian interested in biography and what its study can tell them about what they doâ. - Alun Munslow, Professor of History, Staffordshire UnTrade Review'Anyone who set out to encompass the whole of biographical research in around 200 pages faces a formidable task...Roberts is certainly successful in conveying a sense of the rich diversity of biographical research. This is a book based upon a formidably wide-ranging bibliography together with his own, by no means insignificant, contributions to the field...[the]...reader will be left in no doubt as to the central importance of biographical research and of its legitimate position within the social sciences'. - David Morgan 20020101Table of ContentsSeries editor's forewordIntroductionbiographical researchUses of biographical researchThe life historyAutobiography and biographyAuto/biography and sociologyOral historyThe narrative analysis of livesMemory and autobiographyEthnography and biographical researchConclusionReferencesIndex.

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Book SynopsisSurveys are used extensively in psychology, sociology and business, as well as many other areas, but they are becoming increasingly difficult to conduct. Some segments of the population are hard to sample, some are hard to find, others are hard to persuade to participate in surveys, and still others are hard to interview. This book offers the first systematic look at the populations and settings that make surveys hard to conduct and at the methods researchers use to meet these challenges. It covers a wide range of populations (immigrants, persons with intellectual difficulties, and political extremists) and settings (war zones, homeless shelters) that offer special problems or present unusual challenges for surveys. The team of international contributors also addresses sampling strategies including methods such as respondent-driven sampling and examines data collection strategies including advertising and other methods for engaging otherwise difficult populations.Trade Review'The challenge of doing research with rare and difficult to find populations is shared across all sectors of the research industry. This book offers the first comprehensive treatment of methods specifically designed to meet that challenge.' Reg Baker, Senior Consultant, Market Strategies International'Hard- to-Survey Populations fills a key gap in the survey methods literature. It will be relied upon by both novices and experts.' Stanley Presser, Distinguished University Professor, University of MarylandTable of ContentsPart I. Introduction: 1. Defining hard-to-survey populations; 2. Hard-to-survey populations in comparative perspective; 3. Measuring undercounts for hard-to-survey groups; 4. Counting and estimating hard-to-survey populations in the 2011 Census; 5. A review of quality issues associated with studying hard-to-survey populations; Part II. Conducting Surveys in Difficult Settings: 6. Disaster research: surveying displaced populations; 7. Conducting surveys in areas of armed conflict; 8. Interviewing in disaster-affected areas: lessons learned from post-Katrina surveys of New Orleans residents; 9. Reaching and enumerating homeless populations; 10. 'Where are our costumes?': The All Ireland Traveller Health Study - our Geels 2007–11; Part III. Conducting Surveys with Special Populations: 11. Representing the populations: what general social surveys can learn from surveys among specific groups; 12. Surveying cultural and linguistic minorities; 13. Challenges to surveying immigrants; 14. Ethnographic evaluations on coverage of hard-to-count minorities in US decennial censuses; 15. Methodological and ethical issues arising in carrying out research with children and young people; 16. Challenges in the first ever national survey of people with intellectual disabilities; 17. Conducting research on vulnerable and stigmatized populations; 18. Surveying political extremists; Part IV. Sampling Strategies for the Hard to Survey: 19. Probability sampling methods for hard-to-sample populations; 20. Recent developments of sampling hard-to-survey populations: an assessment; 21. Indirect sampling for hard-to-reach populations; 22. Sampling the Māori population using proxy screening, the Electoral Roll, and disproportionate sampling in the New Zealand Health Survey; 23. Network-based methods for accessing hard-to-survey populations using standard surveys; 24. Link-tracing and respondent-driven sampling; Part V. Data Collection Strategies for the Hard to Survey: 25. Use of paid media to encourage 2010 Census participation among the hard to count; 26. The hard to reach among the poor in Europe: lessons from Eurostat's EU-SILC survey in Belgium; 27. Tailored and targeted designs for hard-to-survey populations; 28. Standardization and meaning in the survey of linguistically diversified populations: insights from the ethnographic observation of linguistic minorities in 2010 Census interviews; 29. Mobilizing hard-to-survey populations to participate fully in censuses and surveys; 30. Finding the hard to reach and keeping them engaged in research.

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Book SynopsisThis book provides a history of the origins of industrial-organizational (I-O) psychology, focusing on the late nineteenth century and early twentieth centuries. Taking an international perspective, The Early Years of Industrial-Organizational Psychology examines the context in which the field emerged, and its origins in the measurement of individual differences. Andrew J. Vinchur covers the initial applications of psychology in advertising, the study of fatigue, and especially employee selection, as well as the role industrial psychology played in World War I and the post-war expansion of the field. He also examines the education of industrial psychologists, their efforts to establish industrial psychology as a profession, and the beginnings of the organizational side of the field.Trade Review'This book provides a compelling look at the extent of research on applied topics in the early years of the 20th century and at how it affected current theory and research. In unfolding industrial and organizational psychology, the author links the work of the applied psychologists to the major historical figures in psychology, showing that the connection between theory and application was closer than is apparent from standard histories. This book is a welcome addition to the history of applied psychology.' B. C. Beins, Choice'This is, in one sense, a very ambitious book, aiming to provide a 'comprehensive picture' of the early years of what is now known as industrial-organizational (IO) psychology. It has a global scope (although the United States receives most attention) and covers roughly half a century, from the late 1800s to the 1930s … it is impressive in its offerings and scope.' Maarten Derksen, IsisTable of Contents1. Work, psychology, and history; 2. Historical context and influence; 3. Measurement, individual differences, and psychological testing; 4. Initial forays into industry; 5. Industrial psychology and the Great War; 6. The post-war expansion of industrial psychology; 7. Employee selection in the 1920s; 8. The education of industrial psychologists; 9. Establishing a profession; 10. The beginnings of organizational psychology; 11. Reflections on the early years of I-O psychology.

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Book SynopsisWe cannot understand contemporary psychology without first researching its history. Unlike other books on the history of psychology, which are chronologically ordered, this Handbook is organized topically. It covers the history of ideas in multiple areas of the field and reviews the intellectual history behind the major topics of investigation. The evolution of psychological ideas is described alongside an analysis of their surrounding context. Readers learn how eminent psychologists draw on the context of their time and place for ideas and practices, and also how innovation in psychology is an ongoing dialogue between past, present, and anticipated future.Trade Review'The famous statement that psychology has a long past but a short history reflects the fact that empirical psychology is a relatively new arrival among the sciences, but that the fascination with psychological topics has been around for thousands of years. This volume by Robert J. Sternberg and Wade E. Pickren successfully melds the discipline's past and history. Readers get a seamless path from philosophy to natural philosophy to scientific psychology across its many sub-disciplines. Unlike standard histories of psychology, this book shows the breadth of psychology as it has evolved to its present state.' Barney Beins, Ithaca College, New York'By assembling an impressive group of specialist scholars, Robert J. Sternberg and Wade E. Pickren have created a volume of great value for both students and researchers. These lucid historical overviews provide an excellent introduction to the history of the major research areas of modern psychology.' Andrew S. Winston, University of Guelph, Canada'The Cambridge Handbook of the Intellectual History of Psychology reveals the rich tapestry of personalities, ideas, theories, controversies, and empirical findings that have contributed to our contemporary understanding of psychology. It is an engaging, highly accessible, and erudite resource that every teacher and student of psychology needs to read.' Dannette Marie, University of Aberdeen'With chapters from leading experts in the sub-disciplines or active researchers in the history of psychology, both students and professionals now have access to a valuable bank of information concerning the historical evolution of specific sub-disciplines' ideas as a way to address the declining knowledge of disciplinary history.' Ingrid Farreras, Hood College, Maryland'The 19 chapters of this multi-author volume cover the intellectual history of various sub-disciplines and concerns of psychology. Each chapter is written by a specialist in the given field … Many chapters will be engaging for those particularly interested in the history of psychology, and the book could well be valued by students and scholars of that history.' K. S. Milar, ChoiceTable of ContentsIntroduction Robert J. Sternberg and Wade E. Pickren; 1. Major paradigms and approaches in psychology John G. Benjafield; 2. Methodology in psychology Daniel J. Denis and Briana Young; 3. Neuroscience in psychology Gary G. Berntson and David Hothersall; 4. Sensation and perception Linda M. Bartoshuk; 5. Attention Michael I. Posner; 6. Learning Mark Bouton and Robert Boakes; 7. Memory Henry L. Roediger, III, and Jeremy K. Yamashiro; 8. Decision making Yuval Erez and Valerie F. Reyna; 9. Creativity Christa L. Taylor, Vlad P. Glavenau, Allison B. Kaufman and James C. Kaufman; 10. Intelligence Robert J. Sternberg; 11. Development Jeremy Burman; 12. Social psychology Cathy Faye; 13. Gender Alexandra Rutherford; 14. Emotion David Devonis; 15. Motivation Richard M. Ryan, Emma L. Bradshaw and Edward L. Deci; 16. Personality and its assessment James N. Butcher; 17. Abnormal psychology Petteri Pietikainen; 18. Psychotherapy Roderick D. Buchanan and Nicholas O. Haslam; 19. Health psychology Wade E. Pickren.

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Book SynopsisIn his new book, Michael Billig uses psychology''s past to argue that nowadays, when we write about the mind, we should use more examples and less theory. He provides a series of historical studies, analysing how key psychological writers used examples. Billig offers new insights about famous analysts of the mind, such as Locke, James, Freud, Tajfel and Lewin. He also champions unfairly forgotten figures, like the Earl of Shaftesbury and the eccentric Abraham Tucker. There is a cautionary chapter on Lacan, warning what can happen when examples are ignored. Marie Jahoda is praised as the ultimate example: a psychologist from the twentieth century with a social and rhetorical imagination fit for the twenty-first. More Examples, Less Theory is an easy-to-read book that will inform and entertain academics and their students. It will particularly appeal to those who enjoy the details of examples rather than the simplifications of big theory.Trade Review'In this highly readable work, Michael Billig makes a compelling argument that good examples do far more to advance and enliven theory than fancy jargon ever could. Students and seasoned writers of psychology will find inspiration in his engaging investigation into some of the most effective communicators in psychology's past.' Alexandra Rutherford, York University, Toronto'A common tendency of psychologists is to describe phenomena through the lens of their own pre-existing theories, thus making phenomena resemble their theories rather than vice versa. In this book, Michael Billig argues for a fundamental reversal of psychology's methodological habits, emphasising the value of 'particularising' psychological insights through the use of richly detailed examples, thus subsuming the general within the specific rather than the opposite. It is a lesson that could invigorate psychology, underscoring how the use of concrete examples helps us see and empathise and remember in ways that theoretical accounts rarely do. Through various case studies, Billig shows how we can learn as well as teach by example.' David E. Leary, University of Richmond'The truth is in the details, not in abstract theory. In his new book, Michael Billig shows us how examples can lead to a better understanding of psychological issues. Analysing the thinking and writing of eminent psychologists, he offers the reader a rich and intriguing alternative history of psychology.' Ruud Abma, Universiteit Utrecht, the Netherlands'This thought-provoking and important book by one of the principal scholars in contemporary psychology and social science makes a strong case for investigating human lives as they are lived, rather than searching for universally applicable theories by means of narrowly controlled experimental research.' Christine Griffin, University of Bath'Billig insists that examples are in rhetorical tension to theory. Here there is something gently subversive about More Examples, [Less Theory]. For the book is not just about writing or the use of examples. It is also a scornful critique of that most sacred of modern academic shibboleths: doing theory and being theoretical.' Michael Marinetto, Times Higher Education'Michael Billig's book puts many basic psychological ideas and approaches in their time and place and describes the minds, personalities, situations and histories of their protagonists. It helps the reader to see where psychology had come from, and why it is like it is. At the end Billig adds a few modest but welcome recommendations for young psychologists. I hope this book becomes a standard text for psychologists early in their studies. I for one should have been greatly helped if Michael Billig's book had been available when I started out.' John Richer, Human Ethology'Starting with the examples of nine very different writers, he selects an exemplary work from each of them and discusses the use (or sometimes neglect) of examples within that work. Furthermore, since most of the chapters are based on material presented in Billig's previously published works, they provide examples of one thoughtful scholar's concerns and interests over a long and productive career.' Raymond E. Fancher, Journal of the History of the Behavioral SciencesTable of Contents1. Introduction; 2. Locke and Shaftesbury: foster father and foster son; 3. Tucker and James: in the same stream of thought; 4. Freud: writing to reveal and conceal himself; 5. Lacan: an ego in pursuit of the ego; 6. Lewin: is there nothing as practical as a good example?; 7. Tajfel and Bernstein: the limits of theory; 8. Jahoda: the ultimate example; 9. Concluding remarks.

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Book Synopsis

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