Qualitative Comparative Analysis With R

This book is a comprehensive guide to qualitative comparative analysis (QCA) using R. Using Boolean algebra to implement principles of comparison used by scholars engaged in the qualitative study of macro social phenomena, QCA acts as a bridge between the quantitative and the qualitative traditions. The QCA package for R, created by the author, facilitates QCA within a graphical user interface. This book provides the most current information on the latest version of the QCA package, which combines written commands with a cross-platform interface. Beginning with a brief introduction to the concept of QCA, this book moves from theory to calibration, from analysis to factorization, and hits on all the key areas of QCA in between. Chapters one through three are introductory, familiarizing the reader with R, the QCA package, and elementary set theory. The next few chapters introduce important applications of the package beginning with calibration, analysis of necessity, analysis of sufficiency, parameters of fit, negation and factorization, and the construction of Venn diagrams. The book concludes with extensions to the classical package, including temporal applications and panel data. Providing a practical introduction to an increasingly important research tool for the social sciences, this book will be indispensable for students, scholars, and practitioners interested in conducting qualitative research in political science, sociology, business and management, and evaluation studies.

Qualitative Comparative Analysis: An Introduction to Research Design and Application is a comprehensive guide to QCA. As QCA becomes increasingly popular across the social sciences, this textbook teaches students, scholars, and self-learners the fundamentals of the method, research design, interpretation of results, and how to present findings.

Social science theory often builds on sets and their relations. Correlation-based methods of scientific enquiry, however, use linear algebra and are unsuited to analyzing set relations. The development of Qualitative Comparative Analysis (QCA) by Charles Ragin has given social scientists a formal tool for identifying set-theoretic connections based on Boolean algebra. As a result, interest in this method has markedly risen among social scientists in recent years. This book offers the first complete introduction on how to perform QCA in the R software environment for statistical computing and graphics with the QCA package. Developed as a comprehensive solution, QCA provides an unprecedented scope of functionality for analyzing crisp, multi-value and fuzzy sets. The reader is not required to have knowledge of R, but the book assumes an understanding of the fundamentals of QCA. Using examples from published work, the authors demonstrate how to make the most of QCA’s wide-ranging capabilities for the reader’s own purposes. Although mainly written for political scientists, this book is also of interest to scholars from other disciplines in the social sciences such as sociology, business, management, organization, anthropology, education and health.

This new addition to the Applied Social Research Methods series is unrivalled, it is written by leaders in the growing field of rigorous, comparative techniques.

"This book offers a hands-on introduction and teaching resource for students, users, and teachers of Qualitative Comparative Analysis (QCA; Ragin, 1987, 2000, 2008b). Given its superior ability to model certain aspects of complexity, QCA has made inroads into virtually every social science discipline and beyond. Software solutions for QCA have also been developing at a fast pace. This book seeks to reduce the time and effort required when we first encounter the logic of not just a new method but also new software. It offers a genuinely simple, intuitive, and hands-on resource for implementing the state-of-the-art protocol of QCA using R, the most advanced software environment for QCA. Our book has an applied and practical focus"--

Some 20 years after the emergence of configurational theory as a key perspective in organization studies in the 1990s, this approach has yet to deliver on its promise. While we know that configurations the relative arrangement of parts and elements - matters, empirical research on configurations is just beginning to deliver on its promise.

The Routledge Reviewer’s Guide to Mixed Methods Analysis is a groundbreaking edited book – the first devoted solely to mixed methods research analyses, or mixed analyses. Each of the 30 seminal chapters, authored by internationally renowned scholars, provides a simple and practical introduction to a method of mixed analysis. Each chapter demonstrates "how to conduct the analysis" in easy-to-understand language. Many of the chapters present new topics that have never been written before, and all chapters offer cutting-edge approaches to analysis. The book contains the following four sections: Part I Quantitative Approaches to Qualitative Data (e.g., factor analysis of text, multidimensional scaling of qualitative data); Part II Qualitative Approaches to Quantitative Data (e.g., qualitizing data, mixed methodological discourse analysis); Part III "Inherently" Mixed Analysis Approaches (e.g., qualitative comparative analysis, mixed methods social network analysis, social media analytics as mixed analysis, GIS as mixed analysis); and Part IV Use of Software for Mixed Data Analysis (e.g., QDA Miner, WordStat, MAXQDA, NVivo, SPSS). The audience for this book includes (a) researchers, evaluators, and practitioners who conduct a variety of research projects and who are interested in using innovative analyses that will allow them to extract more from their data; (b) academics, including faculty who would use this book in their scholarship, as well as in their graduate-level courses, and graduate students who need access to a comprehensive set of mixed analysis tools for their dissertations/theses and other research assignments and projects; and (c) computer-assisted data analysis software developers who are seeking additional mixed analyses to include within their software programs. Chapter 24 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

This working paper gives an overview of Qualitative Comparative Analysis (QCA), a method that enables systematic cross-case comparison of an intermediate number of case studies. It presents an overview of QCA and detailed descriptions of different versions of the method. Based on the experience applying QCA to CIFOR’s Global Comparative Study on REDD+, the paper shows how QCA can help produce parsimonious and stringent research results from a multitude of in-depth case studies developed by numerous researchers. QCA can be used as a structuring tool that allows researchers to share understanding and produce coherent data, as well as a tool for making inferences usable for policy advice. REDD+ is still a young policy domain, and it is a very dynamic one. Currently, the benefits of QCA result mainly from the fact that it helps researchers to organize the evidence generated. However, with further and more differentiated case knowledge, and more countries achieving desired outcomes, QCA has the potential to deliver robust analysis that allows the provision of information, guidance and recommendations to ensure carbon-effective, cost-efficient and equitable REDD+ policy design and implementation