Research methods / methodology Books

Book SynopsisDo you want to understand and apply qualitative research methods in a digital context?This book will help you navigate the complexities of digital access and fluency, ensuring a broad lens on research methodologies.From step-by-step guides to innovative frameworks, each chapter is crafted to give you the confidenceto carry out cutting-edge qualitative research.This book will provide you withThe knowledge you need to advance your qualitative research understanding across all disciplines.A practical reflection of the application of relevant research methodologies.An overview of research ideas, cases, and examples.With a wealth of exercises and examples, this book willbecome a reference point for qualitative research in the digital context by adopting a case-in-point approach for students across all social science disciplines.

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Book SynopsisDo you want to understand how best to embrace the challenges, surprises, and successes of research? This book acts as a journey through research to empower you to make the necessary connections between research and professional practice. From understanding the concepts of research and gathering data, to guiding you in writing it up and achieving positive change, this book will give you:a confident start with clarity on core concepts and getting it right ethically.an insight into diversity in approaches, the impact of context, and how to overcome problems.A better understanding of the realities of social work and social care practice.Step-by-step guidance at each point in the research processEquipped with a wealth of case studies and real-world examples to help you put your knowledge into practice, this book is the perfect companion for students who want to transition to successful practitioner researchers.

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Book SynopsisThe accessible and student-friendly 'how to' for anyone using R for the first time to analyse location-based data.

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Book SynopsisOffering guidance on doing experiments, this Little Quick Fix helps you select the most appropriate experiment for your research, collect and record data, minimise error, and ensure your experiment is ethical and reproducible. Table of ContentsWhat is an experiment? Why do I need to do an experiment for my research? What types of experiment are there? How do I ensure my experiment is ethically appropriate? How do I make my experiment reproducible? How do I minimise error? What types of data should I be collecting in an experiment? How do I collect and record data in an experiment?

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Book SynopsisGuiding you through how to plan your research project, this Little Quick Fix covers everything from how to get started and the stages of research, to avoiding procrastination and staying on track. Like other books in the Little Quick Fix series, this book provides a stand-in for the busy or unavailable supervisor when students are really stuck. It features: Visual, design-led learning Clear, structured, useful pedagogy, with space for notes and workings out A gradual, step-by-step approach for students who are less prepared or out of practice Effective self-directed learning with DIY progress tracking Table of ContentsHow do I get started with planning my project? What does my research journey look like? How do I avoid procrastination? What digital tools can I use to assist me to plan? What resources can I use to plan effectively? Who can support me to bring my plan together? How do I stay on track? How can I use workbook activities to assist me on my research journey?

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Book SynopsisIn an increasingly data-centric world, we all need to know how to read and interpret statistics. But where do we begin? This book breaks statistical terms and concepts down in a clear, straightforward way. From understanding what data are telling you to exploring the value of good storytelling with numbers, it equips you with the information and skills you need to become statistically literate. It also: Dispels misconceptions about the nature of statistics to help you avoid common traps. Helps you put your learning into practice with over 60 Tasks and Develop Your Skills activities. Draws on real-world research to demonstrate the messiness of data and show you a path through it. Approachable and down to earth, this guide is aimed at undergraduates across the social sciences, psychology, business and beyond who want to engage confidently with quantitative methods or statistics.It forms a reassuring aid for anyone looking to understand the foundations of statistics before their course advances, or as a refresher on key content.

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Book SynopsisThe student-focused guide to grounded theory, this book takes you step by step through the whole research process, from creating a research proposal to sharing your findings. Packed with tools to help you understand how grounded theory can be applied at each stage of your research project, the book includes: •Interactive activities and critical thinking questions in every chapter so you can put your knowledge into practice •Case studies written by a wide variety of researchers so you can learn how to navigate real world research from people who have been in your shoes •Templates and checklists to help guide your writing and ensure you don’t miss a step in the research process. Clear, accessible and applied, this book will help you get to grips with the philosophy of grounded theory, understand the nuts and bolts of designing and carrying out your research project, and manage any hurdles along the way. Explore the accompanying online resources, which include PowerPoint slides, additional templates, and weblinks to videos and journal articles relevant to the key concepts in each chapter. Table of ContentsPreparing For Grounded Theory Research Introducing Grounded Theory Philosophical Perspective In Grounded Theory Quality Grounded Theory Processes And Products Planning A Successful Grounded Theory Study Thinking Like A Grounded Theorist Proposing Your Grounded Theory Research Managing Yourself And Others In Grounded Theory Research Producing Grounded Theory Generating And Collecting Data Data Analysis In Grounded Theory From Analysis To Theory Maximising Grounded Theory Impact

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Book SynopsisDo you want to study what people do, the things they say, or what they think?This book offers a lively and questioning account of the essential elements of social research, from defining your research purpose to producing the right output for your audience.Fostering inquisitiveness and ingenuity and drawing on lots of examples and experiences, it will inspire you to think afresh about the various things you might do as a social researcher.It will also: Reveal the lived realities of research, sharing honest and illuminating stories along the way; Draw on plenty of past exercises with studentsto consider how different activities work Demystify the process so you can think for yourself about how to do effective projects. Original, engaging and candid, this book will help any undergraduate or postgraduate navigate the dynamic and challenging landscape of social research with confidence and creativity.

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Book SynopsisA courageous and exciting reconsideration of self, experience and reality and its implications for doing social research differently

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Book SynopsisProviding readers with an accessible, in-depth look at how to synthesize research literature, Conducting Research Literature Reviews: From the Internet to Paper is perfect for students, researchers, marketers, planners, and policymakers who design and manage public and private agencies, conduct research studies, and prepare strategic plans and grant proposals. Bestselling author Arlene Fink shows readers how to explain the need for and significance of research, as well as how to explain a study’s findings. Offering a step-by-step approach to conducting literature reviews, the Fifth Edition features new research, examples, and references from the social, behavioral, and health sciences, expanded coverage of qualitative research, updated and revised meta-analysis procedures, a brand new glossary of key terms, double the number of exercises, and additional examples of how to write reviews.Trade Review"Fink’s tone, level, and style is very approachable and understandable which makes it ideal for my students, most of whom are new to the process of literature reviews." -- Jana Nidiffer"This book provides rich, useful, details on conducting literature review & constructing evidenced based reviews." -- Janet Reid-HectorTable of ContentsPreface Acknowledgments About the Author PART I. Research Design and Sampling Chapter 1: Reviewing the Literature: Why? For Whom? How? What is a Research Literature Review? Why Do One? Gaining Control: Experiments and Observations Systematic, Explicit, Comprehensive, and Reproducible: Four Key Words Choosing an Online Bibliographic Database How Do You Ask for Information? Searching With Boolean Operators Pausing during the Search Changing the Course of the Search Supplementing the Online Search Organizing the Research Literature: Building a Virtual Filing Cabinet Chapter 2: Searching and Screening: The Practical Screen and Methodological Quality Search Screen 1: The Practical Screen Search Screen 2: Methodological Quality Screening Criteria Observational Designs in Brief A Note on Other Designs and Studies: Cross-Sectional Surveys and Consensus Statements Internal and External Validity Criterion for Quality: Sampling The Sampling Unit The Size of the Sample Response Rate PART II. Data Collection, Interventions, Analysis, Results, and Conclusions Chapter 3: Searching and Screening: Methodological Quality Data Collection and Data Sources: Methods and Measures Interventions and Programs: Reviewing the Research Literature to Find out What Works Data Analysis: Statistical Methods in the Research Literature Accounting for Impact Chapter 4: Doing the Review: A Reader’s Guide Chapter Types of Information: Methods and Content Eligibility and Actuality Reporting Standards: Checklists for Research Writing and Reviewing How TREND Was Used in a Literature Review Reliable and Valid Reviews Uniform Data Collection: The Literature Review Survey Questionnaire Uniform Data Collection: Definitions and More Pilot Testing the Review Process Establishing Validity Monitoring Quality Chapter 5: What Did You Find? Synthesizing Results Now that You Have Done It, What Do You Do With It? Descriptive Syntheses or Reviews Meta-Synthesis Meta-Analysis Meta-Analyses in Practice: Examples Glossary Author Index Subject Index

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Book SynopsisRealWorld Evaluation: Working Under Budget, Time, Data, and Political Constraints addresses the challenges of conducting program evaluations in real-world contexts where evaluators and their clients face budget and time constraints. The book is organized around the authors’ seven-step model that has been tested in workshops and practice environments to help the evaluation implementers and managers make the best choices when faced with real world constraints. The Third Edition includes a new chapter on gender equality and women’s empowerment and discussion of digital technology and data science.Trade Review"This book moves the study of evaluation from the theoretical to the practical, so that evaluators can improve their work. It deals with most of the real issues that evaluators face, particularly at the international level." -- John Mathiason"This is one of the most practical textbooks in the field of evaluation that I have encountered. Its recognition of the limitations that affect program evaluation provides students with a realistic understanding of the difficulties in conducting evaluations and how to overcome these difficulties." -- David C. Powell"RealWorld Evaluation moves forward from where other evaluation textbooks stop. RWE challenges the evaluator to ask the difficult questions that can impact the design, implementation, and utilization of the evaluation. RWE then leads the reader through how to find efficient solutions to minimize these constraints." -- Karen McDonnell"RealWorld Evaluation is a must-read for students of program evaluation-the framework and emphasis on practical constraints makes it an invaluable tool for learning the art and science of public policy. -- Amanda Olejarski"This is an invaluable resource for both novice and experienced evaluators. It contains a variety of tools and recommendations to successfully design and implement effective evaluations for any size and type of program." -- Sebastian Galindo"Any research class focusing on real-world evaluation should start with this text; it is comprehensive, well-organized, well-written, and thoroughly practical." -- Jeffrey S. SavageTable of ContentsList of Boxes, Figures, and Tables List of Appendices Foreword by Jim Rugh Preface Acknowledgments About the Authors PART I • THE SEVEN STEPS OF THE REALWORLD EVALUATION APPROACH Chapter 1 • Overview: RealWorld Evaluation and the Contexts in Which It Is Used 1. Welcome to RealWorld Evaluation 2. The RealWorld Evaluation Context 3. The Four Types of Constraints Addressed by the RealWorld Approach 4. Additional Organizational and Administrative Challenges 5. The RealWorld Approach to Evaluation Challenges 6. Who Uses RealWorld Evaluation, for What Purposes, and When? Summary Further Reading Chapter 2 • First Clarify the Purpose: Scoping the Evaluation 1. Stakeholder Expectations of Impact Evaluations 2. Understanding Information Needs 3. Developing the Program Theory Model 4. Identifying the Constraints to Be Addressed by RWE and Determining the Appropriate Evaluation Design 5. Developing Designs Suitable for RealWorld Evaluation Conditions Summary Further Reading Chapter 3 • Not Enough Money: Addressing Budget Constraints 1. Simplifying the Evaluation Design 2. Clarifying Client Information Needs 3. Using Existing Data 4. Reducing Costs by Reducing Sample Size 5. Reducing Costs of Data Collection and Analysis 6. Assessing the Feasibility and Utility of Using New Information Technology (NIT) to Reduce the Costs of Data Collection 7. Threats to Validity of Budget Constraints Summary Further Reading Chapter 4 • Not Enough Time: Addressing Scheduling and Other Time Constraints 1. Similarities and Differences Between Time and Budget Constraints 2. Simplifying the Evaluation Design 3. Clarifying Client Information Needs and Deadlines 4. Using Existing Documentary Data 5. Reducing Sample Size 6. Rapid Data-Collection Methods 7. Reducing Time Pressure on Outside Consultants 8. Hiring More Resource People 9. Building Outcome Indicators Into Project Records 10. New Information Technology for Data Collection and Analysis 11. Common Threats to Adequacy and Validity Relating to Time Constraints Summary Further Reading Chapter 5 • Critical Information Is Missing or Difficult to Collect: Addressing Data Constraints 1. Data Issues Facing RealWorld Evaluators 2. Reconstructing Baseline Data 3. Special Issues Reconstructing Baseline Data for Project Populations and Comparison Groups 4. Collecting Data on Sensitive Topics or From Difficult-to-Reach Groups 5. Common Threats to Adequacy and Validity of an Evaluation Relating to Data Constraints Summary Further Reading Chapter 6 • Political Constraints 1. Values, Ethics, and Politics 2. Societal Politics and Evaluation 3. Stakeholder Politics 4. Professional Politics 5. Political Issues in the Design Phase 6. Political Issues in the Conduct of an Evaluation 7. Political Issues in Evaluation Reporting and Use 8. Advocacy Summary Further Reading Chapter 7 • Strengthening the Evaluation Design and the Validity of the Conclusions 1. Validity in Evaluation 2. Factors Affecting Adequacy and Validity 3. A Framework for Assessing the Validity and Adequacy of QUANT, QUAL, and Mixed-Method Designs 4. Assessing and Addressing Threats to Validity for Quantitative Impact Evaluations 5. Assessing Adequacy and Validity for Qualitative Impact Evaluations 6. Assessing Validity for Mixed-Method (MM) Evaluations 7. Using the Threats-to-Validity Worksheets Summary Further Reading Chapter 8 • Making It Useful: Helping Clients and Other Stakeholders Utilize the Evaluation 1. What Do We Mean by Influential Evaluations and Useful Evaluations? 2. The Underutilization of Evaluation Studies 3. Strategies for Promoting the Utilization of Evaluation Findings and Recommendations Summary Further Reading PART II • A REVIEW OF EVALUATION METHODS AND APPROACHES AND THEIR APPLICATION IN REALWORLD EVALUATION: FOR THOSE WHO WOULD LIKE TO DIG DEEPER Chapter 9 • Standards and Ethics 1. Standards of Competence 2. Professional Standards 3. Ethical Codes of Conduct 4. Issues Summary Further Reading Chapter 10 • Theory-Based Evaluation and Theory of Change 1. Theory-Based Evaluation (TBE) and Theory of Change (TOC) 2. Applications of Program Theory in Program Evaluation 3. Using TOC in Program Evaluation 4. Designing a Theory of Change Evaluation Framework 5. Integrating a Theory of Change Into the Program Management, Monitoring, and Evaluation Cycle 6. Program Theory Evaluation and Causality Summary Further Reading Chapter 11 • Evaluation Designs: The RWE Strategy for Selecting the Appropriate Evaluation Design to Respond to the Purpose and Context of Each Evaluation 1. Different Approaches to the Classification of Evaluation Designs 2. Assessing Causality Attribution and Contribution 3. The RWE Approach to the Selection of the Appropriate Impact Evaluation Design 4. Tools and Techniques for Strengthening the Basic Evaluation Designs 5. Selecting the Best Design for RealWorld Evaluation Scenarios Summary Further Reading Chapter 12 • Quantitative Evaluation Methods 1. Quantitative Evaluation Methodologies 2. Experimental and Quasi-Experimental Designs 3. Strengths and Weaknesses of Quantitative Evaluation Methodologies 4. Applications of Quantitative Methodologies in Program Evaluation 5. Quantitative Methods for Data Collection 6. The Management of Data Collection for Quantitative Studies 7. Data Analysis Summary Further Reading Chapter 13 • Qualitative Evaluation Methods 1. Design 2. Data Collection 3. Data Analysis 4. Reporting 5. Real-World Constraints Summary Further Reading Chapter 14 • Mixed-Method Evaluation 1. The Mixed-Method Approach 2. Rationale for Mixed-Method Approaches 3. Approaches to the Use of Mixed Methods 4. Mixed-Method Strategies 5. Implementing a Mixed-Method Design 6. Using Mixed Methods to Tell a More Compelling Story of What a Program Has Achieved 7. Case Studies Illustrating the Use of Mixed Methods Summary Further Reading Chapter 15 • Sampling Strategies for RealWorld Evaluation 1. The Importance of Sampling for RealWorld Evaluation 2. Purposive Sampling 3. Probability (Random) Sampling 4. Using Power Analysis and Effect Size for Estimating the Appropriate Sample Size for an Impact Evaluation 5. The Contribution of Meta-Analysis 6. Sampling Issues for Mixed-Method Evaluations 7. Sampling Issues for RealWorld Evaluation Summary Further Reading Chapter 16 • Evaluating Complex Projects, Programs, and Policies 1. The Move Toward Complex, Country-Level Development Programming 2. Defining Complexity in Development Programs and Evaluations 3. A Framework for the Evaluation of Complex Development Programs Summary Further Reading Chapter 17 • Gender Evaluation: Integrating Gender Analysis Into Evaluations 1. Why a Gender Focus Is Critical 2. Gender Issues in Evaluations 3. Designing a Gender Evaluation 4. Gender Evaluations With Different Scopes 5. The Tools of Gender Evaluation Summary Further Reading Chapter 18 • Evaluation in the Age of Big Data 1. Introducing Big Data and Data Science 2. Increasing Application of Big Data in the Development Context 3. The Tools of Data Science 4. Potential Applications of Data Science in Development Evaluation 5. Building Bridges Between Data Science and Evaluation Summary Further Reading PART III • MANAGING EVALUATIONS Chapter 19 • Managing Evaluations 1. Organizational and Political Issues Affecting the Design, Implementation, and Use of Evaluations 2. Planning and Managing the Evaluation 3. Institutionalizing Impact Evaluation Systems at the Country and Sector Levels 4. Evaluating Capacity Development Summary Further Reading Chapter 20 • The Road Ahead 1. Conclusions 2. Recommendations Glossary of Terms and Acronyms References Author Index Subject Index

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

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Book SynopsisEducational Research offers a comprehensive, easily digestible introduction to research methods for undergraduate and graduate students. Readers will develop an understanding of the multiple research methods and strategies used in education and related fields, including how to read and critically evaluate published research and how to write a proposal, construct a questionnaire, and conduct an empirical research study on their own. The Seventh Edition maintains the features that made this book a best-seller, including attention-grabbing chapter-opening vignettes, lively examples that engage student interest, a conversational and friendly writing style, and more. With the support of this highly readable text, readers will transform into critical consumers and users of research.

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Book SynopsisDo you want to learn R? This book is built on the premise that anyone with a bit of free time and a healthy curiosity can learn to use R in their studies or at work. The authors focus on using R to do useful things like writing reports, creating data and graphs, accessing datasets collected by others, preparing data, and conducting simple data analysis. In this book you’ll learn how to: install R and RStudio®, and set up an RStudio® project and folders; write an essay with graphs based on simple real-world data using R Markdown; create variables from everyday numeric information and visualize data through ­five types of charts—bar plot, histogram, pie chart, scatter plot, and time series line plot—to identify patterns in the data; write and run R programs, and prepare your data following the tidyverse approach; import external datasets into R, install R data packages, and carry out initial data validity checks; conduct exploratory data analysis through three exercises involving data on voting outcomes, natural resource consumption, and gross domestic product (GDP) via data visualization, correlation coeffi­cient, and simple regression; and write a research paper on the impact of GDP per capita on life expectancy using R Markdown. Student-friendly language and examples (such as binge-watched shows on Netflix, and the top 5 songs on Spotify), cumulative learning, and practice exercises make this a must-have guide for a variety of courses where data are used and reports need to be written. Code and datasets used to carry out the examples in the book are available on an accompanying website.Table of ContentsPreface Why Should You Learn R Too? Who Should Read This Book? What Does This Book Hope to Achieve? What Is in This Book? How Can You Use It? What Is Unique About This Book? Acknowledgments About the Authors CHAPTER 1 • Making Preparations: Software Installation and Project Setup 1.1 Introduction 1.2 How to Download and Install R for Windows 1.3 How to Download and Install R for Mac 1.4 Downloading and Installing RStudio 1.5 Setting Up a Project in RStudio 1.6 Creating Folders Under a Project 1.7 Summary 1.8 References CHAPTER 2 • Writing Your Essay Using R Markdown: Something for Everyone 2.1 Introduction 2.2 The Pros of Using R Markdown 2.3 How to Create an R Markdown File 2.4 How to Write and Format Text in R Markdown 2.5 A Simple Example of an R Markdown Document 2.6 Other Useful Formatting Tricks 2.7 How to Use R Markdown for a Writing Assignment: A Bare-Bones Example 2.8 How to Revise and Improve Your Bare-Bones Essay 2.9 For More Ambitious Readers 2.10 Exercise: Turning Knowledge Into Results 2.11 Summary 2.12 References CHAPTER 3 • Creating Data and Graphs in Your Essays 3.1 Introduction 3.2 Bar Plot I: Graphing the Winners of a Hot Dog Eating Contest 3.3 Bar Plot II: Graphing Winning Lottery Numbers in Texas Pick-3 3.4 Pie Chart: Graphing the Composition of Daily Plays Among Top 5 Songs on Spotify 3.5 Histogram: Graphing the Distribution of LSAT Scores in a Review Class 3.6 Scatter Plot: Graphing the Relationship Between Two Variables— Gas Mileages in the City and on the Highway 3.7 Time Series Plot: Graphing the Changing Pattern of YouTube Video Views 3.8 Useful Tips: Polishing and Exporting Graphs 3.9 Summary 3.10 References CHAPTER 4 • Preparing Your Data 4.1 Introduction 4.2 Writing and Running a Program in R 4.3 Creating Variables and Forming a Dataset 4.4 Manipulating Data Using the dplyr Package 4.5 Chaining Different Data Manipulation Operations: pipe (%>%) 4.6 Missing Values in R: NA 4.7 Summary 4.8 References CHAPTER 5 • Accessing Datasets 5.1 Introduction 5.2 Setting Up an RStudio Project 5.3 Downloading a Dataset 5.4 Installing R Packages for Data Importing 5.5 Importing a Downloaded Dataset in RStudio 5.6 Using R Data Packages: A Simple Example With gapminder 5.7 Using R Data Packages: A More Advanced Example With wbstats 5.8 Using R Data Packages: Finding More R Data Packages 5.9 Where Can You Find More Data? 5.10 Summary 5.11 References CHAPTER 6 • Exploratory Data Analysis: Three Exercises 6.1 Introduction 6.2 Exercise 1: Reporting Results of the 2016 Presidential Primary in King County, Washington 6.3 Exercise 2: Human Use of Natural Resources: Consumption and Biocapacity 6.4 Exercise 3: Exploring the Impact of GDP per Capita on Life Expectancy 6.5 Summary 6.6 References CHAPTER 7 • Writing Your Research Paper Using R: Analyzing the Effect of Economic Development on Life Expectancy

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Book SynopsisThe use of mixed methods designs for conducting research has become a major trend in social science research. Renowned methodological experts Janice Morse and Linda Niehaus present a guide to intermediate and experienced researchers on the possibilities inherent in mixed method research. They offer the basic principles of conducting this kind of study, then examine a wide variety of design options available to the researcher, including their strengths and weaknesses and when to use them. Providing examples from a variety of disciplines, examining potential threats to validity, and showing the relationship between method and theory, the book will be a valuable addition to the methodologist’s library and a useful text in courses in research design.Table of ContentsChapter 1 Mixed Method Design: Who Needs It?; Chapter 2 The Nuts and Bolts of Mixed Method Design; Chapter 3 Theoretical Drive; Chapter 4 Pacing the Components; Chapter 5 The Point of Interface; Chapter 6 Sampling for Mixed Method Designs; Chapter 7 Planning a Mixed Method Project; Chapter 8 Qualitatively-Driven Mixed Method Designs; Chapter 9 Quantitatively-Driven Mixed Method Designs; Chapter 10 Complex Mixed and Multiple Method Designs;

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Book SynopsisThis volume considers the challenges and opportunities of online literature classes and gives instructors tools to ensure students are engaged in the virtual classroom. The ideas shared here are grounded in research, practice, critical self-reflection, and collaboration. Reflecting a diverse collection of practical tips and experiences from colleagues teaching at a variety of institutions, the essays offer readers the chance to inhabit others' classrooms. Contributors discuss building an interactive and inclusive classroom and using hypertext, video lectures, and other asynchronous and synchronous tools in classes whose subjects include, among others, Shakespeare, the Chinese novel, early American literature, speculative fiction, and contemporary American poetry.Trade ReviewAn excellent collection of essays offering a wealth of thoughtful reflections and practical advice." —Glenda Hudson, California State University, Bakersfield

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Book SynopsisResearch Methods in Special Education equips readers with the knowledge needed to make a difference with data. Authors Drs. Brittany L. Hott, Frederick J. Brigham, and Corey Peltier provide access to cutting edge methodologies and related skills researchers need to successfully carry out projects in applied settings. Dedicated chapters focusing on quantitative research synthesis (e.g., meta-analysis, meta-synthesis), single case design, and program evaluation methods allow readers deeply invested in the field of special education to develop a firm foundation, enabling them to ask and answer their socially significant research questions.Written for students in special education teacher prep programs, early career faculty, school administrators, and curriculum specialists, this text includes numerous features that set it apart from other available resources: Dedicated chapters on ethics, establishing effective research partnerships, and evidence-based practice. Cutting-edge program evaluation methods and reporting. Comprehensive coverage of methods commonly used in special education. Detailed information on securing special education funding. Case studies, exemplars, resources, and recommendations for additional reading. Faculty materials including practice problems and activities available at www.efacultylounge.com YouTube videos featuring interviews with authors. The up-to-date research practices in this text are a valuable addition for educators and researchers serving students with disabilities who have a responsibility to support in-school and post-school outcomes. Research Methods in Special Education gives educators the tools to facilitate a deeper understanding of the research process and evidence-based practice.Table of Contents Dedication Acknowledgments About the Authors Contributing Authors Preface Chapter 1 Evidence-Based Practice in Special Education:Constructing an Operational Definition With contributions from Tracy E. Sinclair, PhD, BCBA, LBA Chapter 2Introduction to Special Education Research With contributions from Andrew R. Scheef, PhD;Aleksandra Hollingshead, EdD;and Rachel N. Freedman, MA, MS, BCBA, LABA Chapter 3 Conducting Research in Applied Settings:Practical Strategies for Forming Effective Partnerships With contributions from Reesha Adamson, PhD; Felicity Post, EdD;and Jessica Nelson, EdD, BCBA, LBA Chapter 4Ethical Considerations in Special Education Research With contributions from R. Nicolle Carr, PhD, BCBA-D Chapter 5 Identifying, Locating, and Evaluating Educational Research With contributions from Kathleen M. Randolph, EdD, BCBA-D;Beth A. Jones, PhD; and Lynn E. Gates, MLIS Chapter 6 Systematic Literature Reviews With contributions from John William McKenna, PhD Chapter 7 Correlational Designs With contributions from Sharon Sullivan, PhD Chapter 8 Experimental Designs With contributions from Wilhelmina van Dijk, PhD Chapter 9 Quasi-Experimental Designs Jason C. Chow, PhD Chapter 10 Single Case Research Designs With contributions from Art Dowdy, PhD, BCBA-D and Joshua Jessel, PhD, BCBA-D, LBA Chapter 11 Survey Research With contributions from Nathan A. Stevenson, PhDand Andrew L. Wiley, PhD Chapter 12 Qualitative Research With contributions from Delia E. Racines, PhD Chapter 13 Mixed-Methods Research With contributions from Melissa C. Jenkins, PhD Chapter 14 Program Evaluation With contributions from Maeghan N. Hennessey, PhD;Jason P. Herron, PhD; and Reginald B. Snoddy, MS Chapter 15 Translating Special Education Research to Practice With contributions from Maria B. Peterson-Ahmad, PhD;Randa Keeley, PhD; and Kimberly Floyd, PhD Financial Disclosures Index

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Book Synopsis The Royal Institution has been at the forefront of scientific innovation, discovery and communication since its founding in 1799. Illustrious figures associated with the Royal Institution include Humphry Davy, Michael Faraday and Ernest Rutherford. In this latest addition to Scala's Director's Choice series, Katherine Mathieson shares some of her favourite aspects of the Royal Institution, including Faraday's laboratory, books, pictures and objects. From its Grade 1-listed building in central London, the Royal Institution connects the public with scientists through talks, events and activities for people of all ages and backgrounds, including the famous Christmas Lectures. Founded by Michael Faraday, these lectures were an exciting new way of presenting science to young people and they continue today. This enjoyable, richly illustrated guide unlocks hidden histories of the Royal Institution and reveals how science transforms our lives.

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Book SynopsisThis book asks what it takes for people to encounter one another ethically when practices, worldviews and imaginations clash. It engages over 40 contributors across geographies, disciplines, art forms and practices in a conversation that touches on topics ranging from the climate catastrophe to the disintegration of the welfare state and the erasure of certain bodies from public spaces. It is concerned with how these big' questions play out in small' everyday encounters in classrooms, rehearsal rooms, arts projects, charity events or city markets. The book's polyphonic text does not present answers to its central questions in the way a typical research publication might do. Instead, it creates a flow and invites the reader to join a conversation. By refusing to deliver an argument, the book opens new possibilities for relating to others in the academy and arts.This book is open access under a CC BY ND licence.

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Book SynopsisThe correct design, analysis and interpretation of plant science experiments is imperative for continued improvements in agricultural production worldwide. The enormous number of design and analysis options available for correctly implementing, analysing and interpreting research can be overwhelming. SAS® is the most widely used statistical software in the world and SAS® OnDemand for Academics is now freely available for academic institutions. This is a user-friendly guide to statistics using SAS® OnDemand for Academics, ideal for facilitating the design and analysis of plant science experiments. It presents the most frequently used statistical methods in an easy-to-follow and non-intimidating fashion, and teaches the appropriate use of SAS® within the context of plant science research. This book: - Covers experimental designs and data analysis protocols - Is presented as a how-to guide with many examples - Includes freely downloadable data sets - Examines key topics such as merging data frames, multivariate analysis and linear regression Authored by an experienced teacher of applied plant science statistics, this book assumes no prior background in statistics and guides users through the appropriate methodologies in research. It is an invaluable tool for advanced undergraduate and graduate students, in addition to researchers, extension consultants, faculty and technicians.Table of Contents1: Introduction to Plant Science Research and Experimentation 2: An Introduction to SAS® OnDemand for Academics 3: A Review of Basic Statistics and Terms 4: Plant Science Research and Some Basic Experimental Design Principles 5: Variation and the Analysis of Variance (ANOVA) 6: The Completely Random Design 7: Factorials 8: Contrasts 9: Linear Regression 10: Regression Diagnostics 11: Mean Separation Techniques 12: The Randomized Complete Block Design 13: The Latin Square Design 14: The Split-plot Design and variations (split-split, split-block, strip-plot) 15: Experiments in a Series 16: Expected Mean Squares 17: Analysis of Covariance 18: Non-Parametric Procedures 19: Sampling 20: When Data Doesn’t Behave – Problem Data 21: Presentation of Research Results

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Book SynopsisTraditionally, research impact has been measured by counting citations, and citation-based indicators, such as impact factors. But in the last few years there has been increasing pressure on research and higher education institutions to move beyond citation metrics, and look instead at different forms of impact - at real world impact.Scholarly impact expert Elaine Lasda brings together a cast of innovative contributors from a variety of sectors to look at how impact is measured in ways that go beyond citations in peer-reviewed journal articles. With case studies from publishers, museums, scientific centers and government agencies, the contributors show how using a different mix of traditional bibliometrics, newer altmetrics, and other new measures can provide vital information to support the mission and vision of their organizations. For librarians and information professionals, it is becoming increasingly more important to be able to provide expertise on research impact, influence, productivity and prestige. This exciting new book shows readers how to clarify the importance and relevance of organizational research output, and therefore increase their professional value. With the growing sophistication of research impact analysis, the need for "impact metric literacy" is rising, and this book is a helpful tool for those looking to improve their understanding of research impact.Trade ReviewThis guide consists of seven chapters on the use of metrics to assess the impact of research. Librarians and other researchers from the US present case studies on how a variety of research impact indicators are being used in specialized settings, particularly the physical sciences, social sciences, and humanities. They describe the measurement of the scholarly output of the National Center for Atmospheric Research; metrics used by Michigan Publishing to assess the impact of monographs, journals, and other publications; a methodology to track and measure the impact of research conducted by the University of California Institute of Transportation Studies; bibliometric services used by the Environmental Protection Agency's Library at Research Triangle Park; and the use of altmetrics for tracking attention to published research by museum staff and affiliated research associates at the Natural History Museum of Los Angeles County. -- Copyright 2019 * Portland, OR *Table of Contents1. A Brief History and Overview; Elaine Lasda 2. Scholarly Metrics at NCAR; Keith Maull and Matthew Mayernik 3. New Metrics for Measuring Academic Research Outside the Ivory Tower; Kendra Levine 4. A Breath of Fresh Air: New Bibliometric Services at EPA-RTP Library; Anthony Holderied and Taylor Abernethy 5. Compliance and Defiance: Michigan Publishing’s Early Encounters with Research Impact Metrics; Rebecca Welzenbach and Charles Watkinson 6. Altmetrics in the Museum Environment; Richard P. Hulser 7. What Have We Learned Today? A Synthesis of Cases Presented; Elaine Lasda

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Book SynopsisThis book discusses salient moments of multilingual encounters and brings together contributions focused on the interplay between language use by individuals and societies, and language-related inequalities or opportunities for speakers. The chapters demonstrate how biographical and speaker-centred approaches can contribute to an understanding of linguistic diversity, how researchers can empirically account for lived experiences of languages, and how such accounts are embedded in a larger discussion on social (in)equality. Together the chapters make a powerful case for the importance of speaker-centred methodologies in multilingual and multilingualism research. The book is a rich source of theoretical and methodological reflections and will thus be a valuable resource for both experienced researchers and students beginning to explore biographical research methods.Trade ReviewThis brilliant contribution to language research reframes our understanding of linguistic repertoires, diversity and (in)equality in multilingual societies. Through creative and thought-provoking ideas, it inspires researchers to think differently regarding the creation of knowledge about speakers and their languages. A must-read for anybody interested in speaker-centred approaches to language. * Isabelle LeBlanc, Université de Moncton, Canada *This volume is both a sophisticated theoretical orientation to language biographical research and a practical methodological guide, encompassing the history and on-going development of this vibrant cross-disciplinary area. Researchers seeking to engage with inequalities, shifting categories, and the socio-political and emotional lives of speakers will find inspiration and guidance. * Haley De Korne, University of Oslo, Norway *As a qualitative methodologist who studies multilingualism, I found the volume’s methodological variety enlightening, the theoretical and conceptual lenses enriching, and the examination of minority, Indigenous, deaf, post-apartheid, and post-colonial language users’ lived experiences refreshing. * Melissa B Hauber-Özer, University of Missouri at Columbia, USA, LINGUIST List 34.635 *Table of ContentsFigures and Tables Contributors Acknowledgments Part 1: Introducing Speaking Subjects Chapter 1. Mi-Cha Flubacher and Judith Purkarthofer: Speaking Subjects in Multilingualism Research: Biographical and Speaker-centred Approaches Chapter 2. Judith Purkarthofer: And the Subject Speaks to You: Biographical Narratives as Memories and Stories of the Narratable Self Chapter 3. Tim McNamara: Discourse and the Agency of the Subject in Autobiographical Narratives Chapter 4. Mi-Cha Flubacher: Ethnography as a Speaker-centred Approach? Methodological Reflections Part 2: Empirical Insights Language Portraits as a Starting Ground Chapter 5. Christine Anthonissen: Profiles of Multilingualism: An Analysis of Language Biographies and Linguistic Repertoires of University Students Chapter 6. Maartje De Meulder and Annelies Kusters: Experiencing Multimodal Languaging: The Use of Language Portraits with Deaf and Hearing Multilingual Signers Chapter 7. Ruth Singer: Linguistic Biographies and Language Portraits as Tools for Developing Shared Understandings of Multilingualism with an Indigenous Australian Community Linguistic Repertoires and Language Learning in Time and Space Chapter 8. Xolisa Guzula: Children’s Use of Their Full Linguistic Repertoire to Establish a Social and Linguistic Third Space for Learning: A Case Study of the Stars of Today Literacy Club Chapter 9. Simangele Mashazi and Marcelyn Oostendorp: Belonging: The Interplay of Linguistic Repertoires, Bodies and Space in an Educational Context Chapter 10. Julie Choi: Learning about Multilingual Language Learning Experiences through Language Trajectory Grids Chapter 11. Andrea Sedlaczek: Using Media Diaries to Study Multilingual Media Repertoires: A Pilot Study with Language Learners in a Rural Community Education Setting Addressing Trauma Chapter 12. Julia Sonnleitner: A Past of Flesh and Blood: Chronotopic Agency and Embodiment in Biographic Narrative Chapter 13. Mastura Raschidy: Freedom is Suffering for a Caged Bird: Biographical Approaches and Psychotraumatology Chapter 14. Mascha Dabić: Speaking about the Unspeakable: Interpreter-mediated Psychotherapy for Survivors of War and Torture Part 3: Unsettling and Extending Biographical Research and Speaker-centred Approaches Chapter 15. Ana Deumert, Zolani Kupe and Nkululeko Mabandla: Ilwiimi Zisulungekile: Reflections on Language, Meaning and Communication Chapter 16. Jürgen Spitzmüller: Ideologies of Communication: The Social Link between Actors, Signs and Practices Chapter 17. Anne-Christel Zeiter-Grau: Language Issues? On Collecting Language Biographies without Focusing on Language Chapter 18. Brigitta Busch: A Few Remarks on Working with Auto-Socio-Bio-Ethnography Index

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Book SynopsisIn recent years, crucial questions have been raised about anthropology as a discipline, such as whether ethnography is central to the subject, and how imagination, reality and truth are joined in anthropological enterprises. These interventions have impacted anthropologists and scholars at large. This volume contributes to the debate about the interrelationships between ethnography and anthropology and takes it to a new plane. Six anthropologists with field experience in Egypt, Greece, India, Laos, Mauritius, Thailand and Switzerland critically discuss these propositions in order to renew anthropology for the future. The volume concludes with an Afterword from Tim Ingold.

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Book SynopsisWith surveillance at work extending into the home and the deployment of AI in the workplace already rapidly expanding, concerns have been raised about the ramifications of these developments. Blurring the boundaries between public and private spheres, digital workplace monitoring and digital activity tracking seem set to raise stress levels and undermine trust between employers and employees as they threaten to further infiltrate the world of work. Proposing a clear list of policy options, Ethical AI Surveillance in the Workplace tackles the structural challenges associated with ‘wiring the labour market’, including issues of control, autonomy and voice. From Data Protection Impact Assessments to regulatory sandboxes, and from establishing the right to disconnect to setting up a Code of Ethical Workplace Monitoring, the proposed paths aim to safeguard a responsible deployment of AI-powered monitoring tools within the workplace and protect employees as data subjects whose digital footprints are under constant scrutiny. Wielding the legal, regulatory and institutional tools available, this uniquely structured analysis acts as a comprehensive starting point for discussing these ever-evolving challenges and how they may shape the future of the workplace.Table of ContentsIntroduction; Ron Iphofen Section I. Legal Options Chapter 1. Putting the Employee in the Driving Seat via Reinforced Collective Agreements Chapter 2. Review and Update the Current Legal Framework Chapter 3. Introduce Legislation on Workplace Monitoring Chapter 4. Introduce a Penalty System and Strict Conditionalities Chapter 5. Introduce the Right to obtain an Explanation of the Decision and Challenge It Chapter 6. Introduce the Right of Transparency in Workplace Monitoring Chapter 7. Introduce the Right to Disconnect as a Fundamental Right Chapter 8. Introduce the Right to Health and Safety at Work in the Digital Space Chapter 9. Establish Legislation for the Protection of Whistleblowers and the Development of Effective Communication Corridors in the Workplace Chapter 10. Introduce Review Clauses on Delegated/Implementing acts in Existing Labour Legislation and in any upcoming AI Legislative Proposals Chapter 11. Develop a Workplace/Employee-Specific Data Governance Strategy that Strengthens the Rights to Privacy and Data Protection in the Digital Workplace Chapter 12. Ensure Compliance with a Mandatory Data Protection Impact Assessment for Workplace Monitoring Chapter 13. Redefine the Concept of Consent in the Frame of Workplace Monitoring Chapter 14. Address Psychosocial Risks as an Essential Part of the Occupational Health and Safety (OHS) Legal Framework Section II. Governance Options Chapter 15. Develop a Code of Ethical Workplace Monitoring Chapter 16. Introduce Certification Mechanisms and Standards for Ethical Compliance Chapter 17. Set up an Oversight Body for Workplace Monitoring and other Workplace Governance/Oversight Structures Chapter 18. Establish an Ombudsman for Employment Affairs and Workplace Monitoring Chapter 19. Develop and Establish Procedural Frameworks to Effectively Audit Workplace Algorithmic Systems Chapter 20. Set-up Risk Governance Structures and Algorithmic Risk Assessment Methodologies for Workplace Monitoring Chapter 21. Consider the Particular Risks Related to Keylogging, Workplace Biometrics, Bring Your Own Device (BYOD) Practices Chapter 22. Set up Bodies for Workplace Monitoring Including a High Level Expert Group on Workplace Monitoring Chapter 23. Update any Existing Digital Strategy on Preventing Potential Misuse of AI-Enabled Monitoring Tools Chapter 24. Develop Specialised Training Opportunities for Employers and Employees Alike Section III. Ethics Options Chapter 25. Publicly-Funded Research on Workplace Monitoring should be Subject to a Thorough Ethics Appraisal Chapter 26. Consider Imposing a Moratorium on Certain Workplace Monitoring Tools Chapter 27. A Human in the Loop Approach/Human Oversight Chapter 28. The Explainability and Transparency of AI Monitoring Tools Chapter 29. Draft and Develop an Ethical Charter/Governance Framework Chapter 30. Revisit the Concepts of Worker and of Surveillance Chapter 31. Acknowledge and Address the High Informational Asymmetries Chapter 32. Workplace Monitoring Should Be Considered as High-Risk Chapter 33. Adopt a Broad Definition of AI and Algorithmic Management Chapter 34. Sandboxing Chapter 35. Ethics by Design Chapter 36. Security by design Chapter 37. Misuse/Dual Use Chapter 38. Ethical Leadership Chapter 39. Appeal and Redress Chapter 40. Use ‘Smart’ tools to Handle AI-Related Ethical Risks

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Book SynopsisThe Second Edition of this classic text introduces the main methods, techniques and issues involved in carrying out multilevel modeling and analysis. Snijders and Bosker′s book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book provides step-by-step coverage of: • multilevel theories • ecological fallacies • the hierarchical linear model • testing and model specification • heteroscedasticity • study designs • longitudinal data • multivariate multilevel models • discrete dependent variables There are also new chapters on: • missing data • multilevel modeling and survey weights • Bayesian and MCMC estimation and latent-class models. This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix. This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis. Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen. Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen. Trade Review′Overall, Snijders and Bosker provide an accessible and readable text on the subject of multilevel analysis. It is as much tailored to the needs of advanced quantitative researchers, as to relative beginners in the field. As a reader with limited experience in quantitative research, but an interest in advancing my knowledge and understanding of multilevel analysis, I found this text an ideal introduction to the area′ - Emma SmithMethodspace Book Reviews Club This new edition is still intended for students, teachers, or researchers with an interest in conducting or understanding multilevel analysis. The book is definitely an excellent reference book for researchers working in social sciences, education, environmental sciences, and economic, biological, medical, and health disciplines. -- Yuehua Wu * Zentralblatt Math *Table of ContentsPreface second edition Preface to first edition Introduction Multilevel analysis Probability models This book Prerequisites Notation Multilevel Theories, Multi-Stage Sampling and Multilevel Models Dependence as a nuisance Dependence as an interesting phenomenon Macro-level, micro-level, and cross-level relations Glommary Statistical Treatment of Clustered Data Aggregation Disaggregation The intraclass correlation Within-group and between group variance Testing for group differences Design effects in two-stage samples Reliability of aggregated variables Within-and between group relations Regressions Correlations Estimation of within-and between-group correlations Combination of within-group evidence Glommary The Random Intercept Model Terminology and notation A regression model: fixed effects only Variable intercepts: fixed or random parameters? When to use random coefficient models Definition of the random intercept model More explanatory variables Within-and between-group regressions Parameter estimation ′Estimating′ random group effects: posterior means Posterior confidence intervals Three-level random intercept models Glommary The Hierarchical Linear Model Random slopes Heteroscedasticity Do not force ?01 to be 0! Interpretation of random slope variances Explanation of random intercepts and slopes Cross-level interaction effects A general formulation of fixed and random parts Specification of random slope models Centering variables with random slopes? Estimation Three or more levels Glommary Testing and Model Specification Tests for fixed parameters Multiparameter tests for fixed effects Deviance tests More powerful tests for variance parameters Other tests for parameters in the random part Confidence intervals for parameters in the random part Model specification Working upward from level one Joint consideration of level-one and level-two variables Concluding remarks on model specification Glommary How Much Does the Model Explain? Explained variance Negative values of R2? Definition of the proportion of explained variance in two-level models Explained variance in three-level models Explained variance in models with random slopes Components of variance Random intercept models Random slope models Glommary Heteroscedasticity Heteroscedasticity at level one Linear variance functions Quadratic variance functions Heteroscedasticity at level two Glommary Missing Data General issues for missing data Implications for design Missing values of the dependent variable Full maximum likelihood Imputation The imputation method Putting together the multiple results Multiple imputations by chained equations Choice of the imputation model Glommary Assumptions of the Hierarchical Linear Model Assumptions of the hierarchical linear model Following the logic of the hierarchical linear model Include contextual effects Check whether variables have random effects Explained variance Specification of the fixed part Specification of the random part Testing for heteroscedasticity What to do in case of heteroscedasticity Inspection of level-one residuals Residuals at level two Influence of level-two units More general distributional assumptions Glommary Designing Multilevel Studies Some introductory notes on power Estimating a population mean Measurement of subjects Estimating association between variables Cross-level interaction effects Allocating treatment to groups or individuals Exploring the variance structure The intraclass correlation Variance parameters Glommary Other Methods and Models Bayesian inference Sandwich estimators for standard errors Latent class models Glommary Imperfect Hierarchies A two-level model with a crossed random factor Crossed random effects in three-level models Multiple membership models Multiple membership multiple classification models Glommary Survey Weights Model-based and design-based inference Descriptive and analytic use of surveys Two kinds of weights Choosing between model-based and design-based analysis Inclusion probabilities and two-level weights Exploring the informativeness of the sampling design Example: Metacognitive strategies as measured in the PISA study Sampling design Model-based analysis of data divided into parts Inclusion of weights in the model How to assign weights in multilevel models Appendix. Matrix expressions for the single-level estimators Glommary Longitudinal Data Fixed occasions The compound symmetry models Random slopes The fully multivariate model Multivariate regression analysis Explained variance Variable occasion designs Populations of curves Random functions Explaining the functions 27415.2.4 Changing covariates Autocorrelated residuals Glommary Multivariate Multilevel Models Why analyze multiple dependent variables simultaneously? The multivariate random intercept model Multivariate random slope models Glommary Discrete Dependent Variables Hierarchical generalized linear models Introduction to multilevel logistic regression Heterogeneous proportions The logit function: Log-odds The empty model The random intercept model Estimation Aggregation Further topics on multilevel logistic regression Random slope model Representation as a threshold model Residual intraclass correlation coefficient Explained variance Consequences of adding effects to the model Ordered categorical variables Multilevel event history analysis Multilevel Poisson regression Glommary Software Special software for multilevel modeling HLM MLwiN The MIXOR suite and SuperMix Modules in general-purpose software packages SAS procedures VARCOMP, MIXED, GLIMMIX, and NLMIXED R Stata SPSS, commands VARCOMP and MIXED Other multilevel software PinT Optimal Design MLPowSim Mplus Latent Gold REALCOM WinBUGS References Index

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Book SynopsisThe long-awaited 2nd edition of this best-selling research methods handbook is fully updated and includes brand new coverage of online research methods and techniques, mixed methodology and qualitative analysis. This edition includes two new contributed chapters: Professor Julie McLeod, Sue Childs and Elizabeth Lomas focus on research data management, applying evidence from the recent JISC funded ‘DATUM’ project; Dr Andrew Shenton examines strategies for analysing existing documents. The first to focus entirely on the needs of the information and communications community, this handbook guides the would-be researcher through the variety of possibilities open to them under the heading ‘research’ and provides students with the confidence to embark on their dissertations. The focus here is on the ‘doing’ and although the philosophy and theory of research is explored to provide context, this is essentially a practical exploration of the whole research process with each chapter fully supported by examples and exercises tried and tested over a whole teaching career. Readership: Students of information and communications studies and archives and records management, and practitioners beginning a piece of research.Trade Review"This reference guide outlines the research process for students and practitioners in information studies, communications, records management, knowledge management, and related disciplines. It covers the three major research paradigms in information science, then reviewing the literature, defining the research, the proposal, sampling, ethics, research methods, the type of question the methods can be used for, and how to design it, including case studies, surveys, experimental research, Delphi studies, action research, historical research, and grounded theory. It also details data collection techniques (interviews, questionnaires, observation, diaries, and focus groups), and qualitative and quantitative data analysis and research presentation. The philosophy and theory behind the research is included only for context; emphasis is on the research process itself. This edition adds two chapters by guest authors on data research management and the analysis of existing documents. The chapters on usability testing and ethnography have been expanded to include netnography and other material." -- Reference and Research Book NewsTable of ContentsPART 1: STARTING THE RESEARCH PROCESS1. Major research paradigms Introduction Positivist research Postpositivism and mixed methods research (MMR) Interpretivist research Qualitative or quantitative methodology? Qualitative research design Quantitative research design Mixed methods research Criteria for judging research Establishing trustworthiness in qualitative research Establishing rigour in quantitative research Summary Practical exercise Suggested further reading 2. Reviewing literature Introduction Information searching and retrieval Evaluation Critical analysis Synthesizing the research: developing a theoretical framework Summary Practical exercise Suggested further reading 3. Defining the research Introduction Designing a conceptual framework The research hypothesis Research aims and objectives Summary Practical exercise Suggested further reading 4. The research proposal Why write a proposal? Structure of a research proposal The proposal as a research framework Summary Practical exercise Suggested further reading 5. Sampling Why sample? Population and sample Probability sampling Purposive sampling Summary Practical exercise Suggested further reading 6. Research Data Management - Julie McLeod, Sue Childs and Elizabeth Lomas Introduction – research data and its management challenges Why is research data management important? The research process, data lifecycles and research data management How do I manage my research data? Summary Practical exercise Websites referred to in this chapter Suggested further reading 7. Ethics in research Introduction Gaining access to the field Informed consent Anonymity or confidentiality? Protecting participants Ethics online Summary Practical exercise Suggested further reading 8. Case studies Introduction Phases in case study research Summary Practical exercise Suggested further reading 9. Surveys Introduction Descriptive surveys Explanatory surveys The survey process Summary Practical exercise Suggested further reading 10. Experimental research Introduction The nature of causality The true experiment Quasi-experimental design: the ‘effects study’ Summary Practical exercise Suggested further reading 11. Usability testing Introduction Quasi-experimental usability studies Cognitive walkthroughs Heuristic evaluation Summary Practical exercise Suggested further reading 12. Ethnography Introduction Components of ethnographic study Virtual ethnography – ‘netnography’ Ethics in ethnography Summary Practical exercise Suggested further reading 13. Delphi study Introduction The Delphi process Rules of a Delphi study Modifying a Delphi study Delphi studies and new technologies Summary Practical exercise Suggested further reading 14. Action research Introduction The action research cycle Trustworthiness in action research Action research as reflective practice Summary Practical exercise Suggested further reading 15. Historical research Introduction The research process Summary Practical exercise Suggested further reading 16. Grounded theory: method or analysis? Introduction Defining grounded theory Summary Practical exercise Suggested further reading PART 3: DATA COLLECTION TECHNIQUES17. Interviews Introduction What is the purpose of an interview? The seven stages of the interview process Online interviewing Summary Practical exercise Suggested further reading 18. Questionnaires Introduction Designing questionnaires Developing questions Scale items Forms of questionnaire Summary Practical exercise Suggested further reading 19. Observation Introduction The role of the observer Recording what you see; going in with signposts Summary Practical exercise Suggested further reading 20. Diaries Introduction The purpose of diaries in research Participant diaries The researcher’s log Structure and recording Summary Practical exercise Suggested further reading 21. Focus groups Introduction Purpose of a focus group Organizing a focus group Online focus groups Summary Practical exercise Suggested further reading 22. Analysis of existing, externally created material - Andrew K. Shenton Introduction The different supporting roles of documents LIS research principally based on documents Citation analysis Logs associated with computer software and the use of ICT Summary Practical exercise Suggested further reading PART 4: DATA ANALYSIS AND RESEARCH PRESENTATION23. Qualitative analysis Introduction Phenomenological strategies Ethnographic methods Narrative and discourse analysis Constant comparative analysis Memo writing Presenting qualitative findings Software for qualitative analysis Summary Practical exercise Suggested further reading 24. Quantitative analysis Introduction Levels of measurement Frequency distribution Cross-tabulation Measures of central tendency Measures of dispersion Correlation Displaying data Testing for statistical significance Software for quantitative analysis Summary Practical exercise Suggested further reading 25. Presenting the research Introduction Planning the final report Form and structure Summary Suggested further reading PART 5: GLOSSARY AND REFERENCES Glossary of research terms References

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Book SynopsisThis book gives you the confidence, tools and techniques to produce a first-class dissertation. It offers practical guidelines to planning realistic timetables and structuring every aspect of your work. Find out how to avoid common mistakes and the best way to present your work, and even how to assess your dissertation in the same way as a university or college tutor does.Table of Contents1. Before you start; 2. What is involved?; 3. Getting started; 4. Techniques; 5. Down to details; 6. Writing up; 7. The final stage; Further reading; Glossary; Index;

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Book SynopsisThis is an accessible introduction to the philosophy of social research which relates philosophical ideas to actual research practice. The book makes effective use of illustrations from the UK, US and Europe to examine specific problems and broader issues. The book is intended for undergraduate and postgraduate courses in social research methods within sociology, social policy, politics, social psychology, human geography; philosophy of social science and social theory courses; and as a personal reference for professional researchers.Table of ContentsChapter 1 Introduction; Chapter 2 What is science?; Chapter 3 Philosophy, social science and method; Chapter 4 Knowing the social world; Chapter 5 Objectivity and values in social research; Chapter 6 Philosophical issues in the process of social research; Chapter 7 Poststructuralism, postmodernism and social research; Chapter 8 Conclusion;

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Book Synopsis100 Themed Quizzes with a Foreword by Jenny Ryan of ITVs The Chase

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Book SynopsisGiven the explosion of information and knowledge in the field of Life Sciences, adapting primary literature as materials in course work as part of active learning seems to be more effective in improving scientific literacy among science undergraduates than the pure transmission of content knowledge using traditional textbooks. In addition, students also read research articles as part of undertaking laboratory research projects useful for preparing them for graduate school. As such, a good grasp of reading and analytical skills is needed for students to understand how their research project contributes to the field that they are working in. Such skills are being taught at UK and USA universities. In Asia, this approach in teaching has not yet been as widespread, although similar ideas are beginning to be used in education. Written as a quick guide for undergraduate students and faculty members dealing with scientific research articles as part of a module or research project, this book will be useful, especially in Asia, for students and faculty members as the universities look to incorporating the use of scientific research articles in their undergraduate teaching.For Life Science students, the first time they encounter a primary literature can be rather daunting, though with proper guidance, they can overcome the initial difficulties and become confident in dealing with scientific articles.This guidebook provides a structured approach to reading a research article, guiding the reader step-by-step through each section, with tips on how to look out for key points and how to evaluate each section.Overall, by helping undergraduate students to overcome their anxieties in reading scientific literature, the book will enable the students to appreciate better the process of scientific investigations and how knowledge is derived in science.Table of ContentsIntroduction; How to Search for an Article; Anatomy of a Typical Scientific Article; A Brief Insight into How Scientific Articles Get Published in Journals; The Introduction Section: Background Information on the Topic of Research; More on the Introduction Section: Hypothesis or Question that the Authors were Investigating; The Materials and Methods Section: Reagents and Techniques Used in the Study; The Results Section: What were the Important Observations Made?; The Discussion Section: What were the Main Conclusion(s) Made by the Authors Arising from the Data?; What are Your Views on the Article?; Writing Activities Related to Critiquing an Article; Final Words.

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Book SynopsisIn Seeking a Research-Ethics Covenant in the Social Sciences, Will C. van den Hoonaard chronicles the negative influence that medical research-ethics frameworks have had on social science research-ethics policies. He argues that the root causes of the current ethics disorder in the social sciences are the aggressive audit culture in universities and the privilege accorded to medical research ethics. Van den Hoonaard charts the unique history of research ethics in sociology and anthropology and provides a detailed plan for how to unshackle research ethics in the social sciences from medical frameworks. Central to this plan is an insistence that covenantal ethics be embedded in the professional training of researchers in the social sciences. Based on decades of study, advocacy, and engagement with research-ethics policy at all levels, with a chapter by Marco Marzano (University of Bergamo), the book will be of interest to scholars, policy makers, and administrators who seek to support the full potential of social science research.Trade Review"Will C. van den Hoonaard makes a bold and important contribution to research on ethics in social science disciplines. I believe it will inform productive discussions in university ethics committees as well as being of interest to readers exploring broader questions about how the production of knowledge can or should be regulated." Fiona Nicoll, Professor, University of AlbertaTable of ContentsAcknowledgements Preface 1 | The Climate of Research-Ethics Review in the Social Sciences 2 | A Robust Audit Culture and Its Aversion to Diversity 3 | The Capture of the Social Sciences by the Medical Ethics Framework 4 | The Anthropological Stance in Ethical Research 5 | Sociology and the New Ethics Disorder (by Marco Marzano) 6 | Current Debates in the Research-Ethics Community 7 | Towards a New Approach in the Social Sciences Appendix: The New Brunswick Declaration on Ethics in Research Notes References Index

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Book SynopsisA brief, authoritative introduction to field experimentation in the social sciences.Table of ContentsPreface Chapter 1: Introduction Chapter 2: Causal Inference and Experimentation Chapter 3: Sampling Distributions, Statistical Inference, and Hypothesis Testing Chapter 4: Using Covariates in Experimental Design and Analysis Chapter 5: One-Sided Noncompliance Chapter 6: Two-Sided Noncompliance Chapter 7: Attrition Chapter 8: Interference between Experimental Units Chapter 9: Heterogeneous Treatment Effects Chapter 10: Mediation Chapter 11: Integration of Research Findings Chapter 12: Instructive Examples of Experimental Design Chapter 13: Writing an Experimental Proposal, Research Report, and Journal Article Appendix A: Protection of Human Subjects Appendix B: Suggested Field Experiments for Class Projects

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Book SynopsisThis practical, step-by-step guide explains the most important principles for using a generic approach to descriptive-interpretive qualitative research. Table of ContentsSeries Foreword by Clara E. Hill and Sarah Knox1. Why a Generic Descriptive-Interpretive Approach to Qualitative Research?2. Designing the Study3. Data Collection4. A Framework of Key Modes of Qualitative Data Analysis5. Writing the Manuscript6. Methodological Integrity7. Summary and ConclusionsAppendix. Example StudiesReferences

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Book SynopsisIn this step-by-step guide to writing autoethnography, the author describes and illustrates the essential features and practices of this qualitative research method. Table of ContentsChapter 1. Conceptual Foundations of Autoethnography Chapter 2. Doing Autoethnography (Design and Data Collection) Chapter 3. Writing Autoethnography Chapter 4. Process and Craft Chapter 5. Variations on the Method Chapter 6. Methodological Integrity, Summary, and Conclusions References Appendix A. Exemplars

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Book SynopsisCritical realism helps researchers to extend and clarify their analyses. This original text draws on international examples of health and illness research across the life course, from small studies to large trials, to show how versatile critical realism can be in validating research and connecting it to policy and practice.Table of ContentsIntroduction Rethinking theories: the basis of practical research and problems with paradigms Basic critical realist concepts Structure and agency: making connections Health and illness research: value-free or value-laden? Four planes of social being: more connections Researching transformative change over time The point is to change it: connecting research to policy and practice

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Book SynopsisWritten in an accessible, practical and jargon-free style, this useful book informs and inspires researchers by showing readers why, when, and how to use creative methods in their research.Trade Review“Inviting the researcher to make the research process attractively creative, Kara extends the scope of the western research tradition, while simultaneously demonstrating rapid growth in the creative research sphere.” Chats Devroop, University of KwaZulu-Natal"Thank goodness for Helen Kara's work. Written in an easily accessible style, Kara tells it like it is and guides her readers beyond her own text to further reading and exploration. In terms of getting bang for one's buck, this is exactly what a second edition should be - substantively re-worked from the first edition, with considerable new content and chapters." Sharon Inglis, Staffordshire University"A really insightful book with broad coverage of creative methods, an excellent 'go to' text for students who are considering using creative research methods. I find particularly valuable the inclusion of reflective questions at the end of each chapter, this will encourage students to think about the applications of what they are reading in their own project contexts." Louise Gascoine, Durham UniversityTable of ContentsIntroducing Creative Research Creative Research Methods in Practice Transformative Research Frameworks and Indigenous Research Creative Research Methods and Ethics Creative Thinking Arts-Based and Embodied Data Gathering Using Technology and Mixing Methods in Data Gathering Arts-Based and Embodied Data Analysis Using Technology and Mixing Methods in Data Analysis Arts-Based and Embodied Research Reporting Using Technology and Mixing Methods in Research Reporting Arts-Based and Embodied Presentation Using Technology and Mixing Methods in Presentation Research Into Practice Conclusion

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Book SynopsisHistory through material culture is a unique, step-by-step guide for students and researchers who wish to use objects as historical sources.Responding to the significant, scholarly interest in historical material culture studies, this book makes clear how students and researchers ready to use these rich material sources can make important, valuable and original contributions to history.Written by two experienced museum practitioners and historians, the book recognises the theoretical and practical challenges of this approach and offers clear advice on methods to get the best out of material culture research. With a focus on the early modern and modern periods, this volume draws on examples from across the world and demonstrates how to use material culture to answer a range of enquiries, including social, economic, gender, cultural and global history.Table of ContentsIntroduction 1 Approaches to the material world 2 Planning a research project 3 Developing a methodology 4 Locating sources: understanding museum collections and other repositories 5 Analysing sources 6 Writing up findings Afterword Index

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Book SynopsisThis is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations.Can octopuses feel pain and pleasure? What about crabs, shrimps, insects or spiders? How do we tell whether a person unresponsive after severe brain injury might be suffering? When does a fetus in the womb start to have conscious experiences? Could there even be rudimentary feelings in miniature models of the human brain, grown from human stem cells? And what about AI?These are questions about the edge of sentience, and they are subject to enormous, disorienting uncertainty. We desperately want certainty, but it is out of reach. The stakes are immense, and neglecting the risks can have terrible costs. We need to err on the side of caution, yet it''s often far from clear what ''erring on the side of caution'' should mean in practice. When are we going too far? When are we not doing enough?The Edge of Sentience presents a comprehensive precautionary framework designed to help us reach ethically sound, evidence-based decisions despite our uncertainty. The book is packed with specific, detailed proposals intended to generate discussion and debate. At no point, however, does it offer any magic tricks to make our uncertainty go away. Uncertainty is with us for the long term. We must manage our uncertainty by taking precautions that are proportionate to the risks. It''s time to start debating what those steps should be.

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Book SynopsisGary Thomas is Professor of Inclusion and Diversity at the University of Birmingham, UK, having previously worked as a teacher and an educational psychologist.Table of ContentsPART 1: Planning PART 2: Groundwork PART 3: Building a scaffold PART 4: Fieldwork: finding the data PART 5: Analysing the data PART 6: Writing up research.

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