Studying Complex Interactions and Outcomes Through Qualitative Comparative Analysis: A Practical Guide to Comparative Case Studies and Ethnographic Data Analysis offers practical, methodological, and theoretically robust guidelines to systematically study the causalities, dynamics, and outcomes of complex social interactions in multiple source data sets. It demonstrates how to convert data from multisited ethnography of investment politics, mobilizations, and citizen struggles into a Qualitative Comparative Analysis (QCA). In this book, Markus Kroeger focuses on how data collected primarily via multisited political ethnography, supplemented by other materials and verified by multiple forms of triangulation, can be systematically analyzed through QCA. The results of this QCA offer insight on how to study the political and economic outcomes in natural resource conflicts, across different contexts and political systems. This book applies the method in practice using examples from the author's own research. With a focus on social movement studies, it shows how QCA can be used to analyze a multiple data source database, that includes results from multiple case studies. This book is a practical guide for researchers and students in social movement studies and other disciplines that produce ethnographic data from multiple sources on how to analyze complex databases through the QCA.

Case study research is a versatile approach that allows for different data sources to be combined, with its main purpose being theory development. This book goes a step further by combining different case study research designs, informed by the authors' extensive teaching and research experience. It provides an accessible introduction to case study research, familiarizes readers with different archetypical and sequenced designs, and describes these designs and their components using both real and fictional examples. It provides thought-provoking exercises, and in doing so, prepares the reader to design their own case study in a way that suits the research objective. Written for an academic audience, this book is useful for students, their supervisors and professors, and ultimately any researcher who intends to use, or is already using, the case study approach.

Cases and Stories of Transformative Action Research builds on its companion book, Principles and Methods of Transformative Action Research, by describing and analyzing dozens of examples of successful action research efforts pursued in the past five decades by students and faculty of the Western Institute for Social Research. Some projects are large-scale, and some are modest interventions in the everyday lives of those participating. Some are formal organizational efforts; others are the results of individual or small group initiatives. Included are chapters on community needs assessments and innovative grassroots approaches to program evaluation; the challenges of improving our decision-making during the crisis of the COVID-19 pandemic; strategies of intellectual activism in addressing the growing problem of workplace bullying; action research to preserve and share the history of the Omaha tribe; and plans for an innovative school-based project based on collaborative action-and-inquiry between students and Artificial Intelligence. In addition, there are a number of detailed stories about the use of transformative action research in such areas as somatic and trauma counseling, ethnic studies, health disparities, gender differences, grassroots popular education, and the improvement of statewide steps for preventing child abuse, among many others. This book can serve as an undergraduate or graduate social sciences text on research methods. It is also a guidebook for action-oriented research by academics, professionals, and lay people alike.

Mastering the Semi-Structured Interview and Beyond offers an in-depth and captivating step-by-step guide to the use of semi-structured interviews in qualitative research. By tracing the life of an actual research project-an exploration of a school district's effort over 40 years to address racial equality-as a consistent example threaded across the volume, Anne Galletta shows in concrete terms how readers can approach the planning and execution of their own new research endeavor, and illuminates unexpected real-life challenges they may confront and how to address them. The volume offers a close look at the inductive nature of qualitative research, the use of researcher reflexivity, and the systematic and iterative steps involved in data collection, analysis, and interpretation. It offers guidance on how to develop an interview protocol, including the arrangement of questions and ways to evoke analytically rich data. Particularly useful for those who may be familiar with qualitative research but have not yet conducted a qualitative study, Mastering the Semi-Structured Interview and Beyond will serve both undergraduate and graduate students as well as more advanced scholars seeking to incorporate this key methodological approach into their repertoire.

The Data Book: Collection and Management of Research Data is the first practical book written for researchers and research team members covering how to collect and manage data for research. The book covers basic types of data and fundamentals of how data grow, move and change over time. Focusing on pre-publication data collection and handling, the text illustrates use of these key concepts to match data collection and management methods to a particular study, in essence, making good decisions about data. The first section of the book defines data, introduces fundamental types of data that bear on methodology to collect and manage them, and covers data management planning and research reproducibility. The second section covers basic principles of and options for data collection and processing emphasizing error resistance and traceability. The third section focuses on managing the data collection and processing stages of research such that quality is consistent and ultimately capable of supporting conclusions drawn from data. The final section of the book covers principles of data security, sharing, and archival. This book will help graduate students and researchers systematically identify and implement appropriate data collection and handling methods.

Scientometrics for the Humanities and Social Sciences is the first ever book on scientometrics that deals with the historical development of both quantitative and qualitative data analysis in scientometric studies. It focuses on its applicability in new and emerging areas of inquiry. This important book presents the inherent potential for data mining and analysis of qualitative data in scientometrics. The author provides select cases of scientometric studies in the humanities and social sciences, explaining their research objectives, sources of data and methodologies. It illustrates how data can be gathered not only from prominent online databases and repositories, but also from journals that are not stored in these databases. With the support of specific examples, the book shows how data on demographic variables can be collected to supplement scientometric data. The book deals with a research methodology which has an increasing applicability not only to the study of science, but also to the study of the disciplines in the humanities and social sciences.

Meta-analysis is the application of statistics to combine results from multiple studies and draw appropriate inferences. Its use and importance have exploded over the last 25 years as the need for a robust evidence base has become clear in many scientific areas, including medicine and health, social sciences, education, psychology, ecology, and economics. Recent years have seen an explosion of methods for handling complexities in meta-analysis, including explained and unexplained heterogeneity between studies, publication bias, and sparse data. At the same time, meta-analysis has been extended beyond simple two-group comparisons of continuous and binary outcomes to comparing and ranking the outcomes from multiple groups, to complex observational studies, to assessing heterogeneity of effects, and to survival and multivariate outcomes. Many of these methods are statistically complex and are tailored to specific types of data. Key features Rigorous coverage of the full range of current statistical methodology used in meta-analysis Comprehensive, coherent, and unified overview of the statistical foundations behind meta-analysis Detailed description of the primary methods for both univariate and multivariate data Computer code to reproduce examples in chapters Thorough review of the literature with thousands of references Applications to specific types of biomedical and social science data Supplementary website with code, data, sample chapters, and errata This book is for a broad audience of graduate students, researchers, and practitioners interested in the theory and application of statistical methods for meta-analysis. It is written at the level of graduate courses in statistics, but will be of interest to and readable for quantitative scientists from a range of disciplines. The book can be used as a graduate level textbook, as a general reference for methods, or as an introduction to specialized topics using state-of-the art methods.

This comprehensive volume explores the set of theoretical, methodological, ethical and analytical issues that shape the ways in which visual qualitative research is conducted in psychology. Using visual data such as film making, social media analyses, photography and model making, the book uniquely uses visual qualitative methods to broaden our understanding of experience and subjectivity. In recent years, visual research has seen a growing emphasis on the importance of culture in experience-based qualitative methods. Featuring contributors from diverse research backgrounds including narrative psychology, personal construct theory and psychoanalysis, the book examines the potential for visual methods in psychology. In each chapter of the book, the contributors explore and address how a visual approach has contributed to existing social and psychological theory in their line of research. The book provides up-to-date insights into combining methods to create new multi-modal methodologies, and analyses these with psychology-specific questions in mind. It covers topics such as sexuality, identity, group processes, child development, forensic psychology, race and gender, and would be the ideal companion for those studying or undertaking research in disciplines like psychology, sociology and gender studies.

This book offers a refreshing new approach to mental health by showing how 'mental health' behaviours, lived experiences, and our interventions arise from our social worlds and not from our neurophysiology gone wrong. It is part of a trilogy which offers a new way of doing psychology focusing on people's social and societal environments as determining their behaviour, rather than internal and individualistic attributions. 'Mental health' behaviours are carefully analysed as ordinary behaviours which have become exaggerated and chronic because of the bad life situations people are forced to endure, especially as children. This shifts mental health treatments away from the dominance of psychology and psychiatry to show that social action is needed because many of these bad life situations are produced by our modern society itself. By providing new ways for readers to rethink everything they thought they knew about mental health issues and how to change them, Bernard Guerin also explores how by changing our environmental contexts (our local, societal, and discursive worlds), we can improve mental health interventions. This book reframes 'mental health' into a much wider social context to show how societal structures restrict our opportunities and pathways to produce bad life situations, and how we can also learn from those who manage to deal with the very same bad life situations through crime, bullying, exploitation, and dropping out of mainstream society, rather than through the 'mental health' behaviours. By merging psychology and psychiatry into the social sciences, Guerin seeks to better understand how humans operate in their social, cultural, economic, patriarchal, discursive, and societal worlds, rather than being isolated inside their heads with a 'faulty brain', and this will provide fascinating reading for academics and students in psychology and the social sciences, and for counsellors and therapists.

Second Edition offers a comprehensive presentation of scientific sampling principles and shows how to design a sample survey and analyze the resulting data. Demonstrates the validity of theorems and statements without resorting to detailed proofs.

Statistical Concepts-A Second Course presents the last 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for second and upper-level statistics courses, this book highlights how statistics work and how best to utilize them to aid students in the analysis of their own data and the interpretation of research results. In this new edition, Hahs-Vaughn and Lomax discuss sensitivity, specificity, false positive and false negative errors. Coverage of effect sizes has been expanded upon and more organizational features (to summarize key concepts) have been included. A final chapter on mediation and moderation has been added for a more complete presentation of regression models. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R. This book acts as a clear and accessible instructional tool to help readers fully understand statistical concepts and how to apply them to data. It is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral science disciplines.

Collecting and analyzing data on unemployment, inflation, and inequality help describe the complex world around us. When published by the government, such data are called official statistics. They are reported by the media, used by politicians to lend weight to their arguments, and by economic commentators to opine about the state of society. Despite such widescale use, explanations about how these measures are constructed are seldom provided for a non-technical reader. This Measuring Society book is a short, accessible guide to six topics: jobs, house prices, inequality, prices for goods and services, poverty, and deprivation. Each relates to concepts we use on a personal level to form an understanding of the society in which we live: We need a job, a place to live, and food to eat. Using data from the United States, we answer three basic questions: why, how, and for whom these statistics have been constructed. We add some context and flavor by discussing the historical background. This book provides the reader with a good grasp of these measures. Chaitra H. Nagaraja is an Associate Professor of Statistics at the Gabelli School of Business at Fordham University in New York. Her research interests include house price indices and inequality measurement. Prior to Fordham, Dr. Nagaraja was a researcher at the U.S. Census Bureau. While there, she worked on projects relating to the American Community Survey.

Designing a research project is possibly the most difficult task a dissertation writer faces. It is fraught with uncertainty: what is the best subject? What is the best method? For every answer found, there are often multiple subsequent questions, so it's easy to get lost in theoretical debates and buried under a mountain of literature. This book looks at literature review in the process of research design, and how to develop a research practice that will build skills in reading and writing about research literature-skills that remain valuable in both academic and professional careers. Literature review is approached as a process of engaging with the discourse of scholarly communities that will help graduate researchers refine, define, and express their own scholarly vision and voice. This orientation on research as an exploratory practice, rather than merely a series of predetermined steps in a systematic method, allows the researcher to deal with the uncertainties and changes that come with learning new ideas and new perspectives. The focus on the practical elements of research design makes this book an invaluable resource for graduate students writing dissertations. Practicing research allows room for experiment, error, and learning, ultimately helping graduate researchers use the literature effectively to build a solid scholarly foundation for their dissertation research project.

Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books. Numerous pedagogical features further facilitate understanding: examples of published research demonstrate the applicability of each chapter's content; flowcharts assist in choosing the most appropriate procedure; end-of-chapter lists of important formulas highlight key ideas and assist readers in locating the initial presentation of equations; useful programming code and tips are provided throughout the book and in associated resources available online, and extensive sets of exercises help develop a deeper understanding of the subject. Detailed solutions for some of the exercises and realistic data sets are included on the website (DesigningExperiments.com). The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. The book and its companion website with web apps, tutorials, and detailed code are ideal for students and researchers seeking the optimal way to design their studies and analyze the resulting data.

First published in 1996. This book is designed to help students acquire basic skills needed to comprehend social and behavioural science research reports. These skills are needed to understand research results that we confront in our everyday lives in magazines, newspapers, on television, and elsewhere. It includes a guide and a workbook.

Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM's SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text: Explains a conceptual framework for each statistical procedure Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure Details SPSS paths for conducting various analyses Discusses the interpretations of statistical results and conclusions of the research With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.

The Clinician's Guide to Treating Health Anxiety: Diagnosis, Mechanisms, and Effective Treatment provides mental health professionals with methods to better identify patients with health anxiety, the basic skills to manage it, and ways to successfully adapt cognitive behavioral therapy to treat it. The book features structured diagnostic instruments that can be used for assessment, while also underscoring the importance of conducting a comprehensive functional analysis of the patient's problems. Sections cover refinements in assessment and treatment methods and synthesize existing literature on etiology and maintenance mechanisms. Users will find an in-depth look at who develops health anxiety, what the behavioral and cognitive mechanisms that contribute to it are, why it persists in patients, and how it can be treated.

Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.

Experience Sampling in Mental Health Research provides comprehensive and user-friendly guidance on when and how to apply this methodology in the assessment of clinical populations. Divided into three sections, the book offers step-by-step instruction on how to design, develop and implement an ESM study, as well as advice on how this approach might be adapted for common mental health difficulties. With an eye to the future of this type of research, the contributors also consider how ESM might be adapted for use as a form of clinical assessment and intervention. Experience Sampling in Mental Health Research combines the knowledge and expertise of leading international experts in the field, and will be helpful for students, researchers and clinicians wishing to start or develop their understanding of this methodology.

Compositional Data Analysis in Practice is a user-oriented practical guide to the analysis of data with the property of a constant sum, for example percentages adding up to 100%. Compositional data can give misleading results if regular statistical methods are applied, and are best analysed by first transforming them to logarithms of ratios. This book explains how this transformation affects the analysis, results and interpretation of this very special type of data. All aspects of compositional data analysis are considered: visualization, modelling, dimension-reduction, clustering and variable selection, with many examples in the fields of food science, archaeology, sociology and biochemistry, and a final chapter containing a complete case study using fatty acid compositions in ecology. The applicability of these methods extends to other fields such as linguistics, geochemistry, marketing, economics and finance. R Software The following repository contains data files and R scripts from the book https://github.com/michaelgreenacre/CODAinPractice. The R package easyCODA, which accompanies this book, is available on CRAN -- note that you should have version 0.25 or higher. The latest version of the package will always be available on R-Forge and can be installed from R with this instruction: install.packages("easyCODA", repos="http://R-Forge.R-project.org").

Designing and conducting experiments involving human participants requires a skillset different from that needed for statistically analyzing the resulting data. The Design and Conduct of Meaningful Experiments Involving Human Participants combines an introduction to scientific culture and ethical mores with specific experimental design and procedural content. Author R. Barker Bausell assumes no statistical background on the part of the reader, resulting in a highly accessible text. Clear instructions are provided on topics ranging from the selection of a societally important outcome variable to potentially efficacious interventions to the conduct of the experiment itself. Early chapters introduce the concept of experimental design in an intuitive manner involving both hypothetical and real-life examples of how people make causal inferences. The fundamentals of formal experimentation, randomization, and the use of control groups are introduced in the same manner, followed by the presentation and explanation of common (and later, more advanced) designs. Replete with synopses of examples from the journal literature and supplemented by 25 experimental principles, this book is designed to serve as an interdisciplinary supplementary text for research-methods courses in the educational, psychological, behavioral, social, and health sciences. It also serves as an excellent primary text for methods seminar courses.

Practice-Based Research shows mental-health practitioners how to establish viable and productive research programs in routine clinical settings. Chapters written by experts in practice-based research use real-world examples to help clinicians work through some of the most common barriers to research output in these settings, including lack of access to institutional review boards, lack of organizational support, and limited access to financial resources. Specialized chapters also provide information on research methods and step-by-step suggestions tailored to a variety of practice settings. This is an essential volume for clinicians interested in establishing successful, long-lasting practice-based research programs.

Bodies that Birth puts birthing bodies at the centre of questions about contemporary birth politics, power, and agency. Arguing that the fleshy and embodied aspects of birth have been largely silenced in social science scholarship, Rachelle Chadwick uses an array of birth stories, from diverse race-class demographics, to explore the narrative entanglements between flesh, power, and sociomateriality in relation to birth. Adopting a unique theoretical framework incorporating new materialism, feminist theory, and a Foucauldian 'analytics of power', the book aims to trace and trouble taken-for-granted assumptions about birthing bodies. Through a diffractive and dialogical approach, the analysis highlights the interplay between corporeality, power, and ideologies in the making of birth narratives across a range of intersectional differences. The book shows that there is no singular birthing body apart from sociomaterial relations of power. Instead, birthing bodies are uncertain zones or unpredictable assortments of physiology, flesh, sociomateriality, discourse, and affective flows. At the same time, birthing bodies are located within intra-acting fields of power relations, including biomedicine, racialized patriarchy, socioeconomics, and geopolitics. Bodies that Birth brings the voices of women from different sociomaterial positions into conversation. Ultimately, the book explores how attending to birthing bodies can vitalize global birth politics by listening to what matters to women in relation to birth. This is fascinating reading for researchers, academics, and students from across the social sciences.