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Qualitative Comparative Analysis in Mixed Methods Research and Evaluation provides a user-friendly introduction for using Qualitative Comparative Analysis (QCA) as part of a mixed methods approach to research and evaluation. Offering practical, in-depth, and applied guidance for this unique analytic technique that is not provided in any current mixed methods textbook, the chapters of this guide skillfully build upon one another to walk researchers through the steps of QCA in logical order. To enhance and further reinforce learning, authors Leila C. Kahwati and Heather L. Kane provide supportive learning objectives, summaries, and exercises, as well as author-created datasets for use in R via the companion site. Qualitative Comparative Analysis in Mixed Methods Research and Evaluation is Volume 6 in SAGE’s Mixed Methods Research Series. To learn more about each text in the series, please visit sagepub.com/mmrs.
Qualitative Comparative Analysis in Mixed Methods Research and Evaluation provides a user-friendly introduction for using Qualitative Comparative Analysis (QCA) as part of a mixed methods approach to research and evaluation. Offering practical, in-depth, and applied guidance for this unique analytic technique that is not provided in any current mixed methods textbook, the chapters of this guide skillfully build upon one another to walk researchers through the steps of QCA in logical order. To enhance and further reinforce learning, authors Leila C. Kahwati and Heather L. Kane provide supportive learning objectives, summaries, and exercises, as well as author-created datasets for use in R via the companion site. Qualitative Comparative Analysis in Mixed Methods Research and Evaluation is Volume 6 in SAGE’s Mixed Methods Research Series.
In recent years a great deal of time and effort has been expended toward the development of qualitative methods which retain the advantages of case study and small-n methods, but which ameliorate the various problems (lack of transparency, excessive subjectivity, etc.) Qualitative Comparative Analysis (QCA) is one of the more commonly used examples. QCA allows qualitative researchers to evaluate whether specific factors (conditions) and/or constellations of conditions are necessary, sufficient, or both for a given outcome. While QCA represents an important advance in political science methodology, its primary contributions are confined to how conclusions are drawn from data. Even with a rigorous application of QCA methodology, considerable subjectivity remains in how conditions and outcomes are coded. This is the gap we hope to address with this paper. Taking our inspiration from mixed-methods research design, we develop a new version of QCA, which we call Latent Condition-QCA (LC-QCA). The method relies on the fact that even in studies with a small number of units of analysis, researchers often have a much larger number of units of observation. That is, qualitative coding at higher levels is often based on the aggregation of lower-level units within cases (documents nested with countries, speeches nested within leaders, etc.) In LC-QCA, subjective qualitative coding is conducted at the lowest level of abstraction possible. It is assumed that the probability of observing distinct patterns of these codings is conditional upon the presence or absence of latent conditions. We further assume that conditions at the unit of observation level are predicted by latent conditions at the unit-of-analysis level. We then use hierarchical latent class analysis (HLCA) to assign conditions to units of analysis and observation. These condition assignments are then used to conduct QCA in the normal fashion. The logic used to develop LC-QCA demonstrates a framework for the advancement of social science methods through a true mixture of quantitative and qualitative methods.
Seminar paper from the year 2006 in the subject Business economics - General, grade: Sehr Gut, Vienna University of Economics and Business (Europainstitut), course: Qualitative Methoden, language: English, abstract: Traditionally most social researchers either employ purely qualitative or quantitative methods, even though a mixed method strategy may promise better results. The present paper introduces Qualitative Comparative Analysis (QCA) as a mixed method alternative for data analysis. It may be of particular value when dealing with small-n case studies, which typically do not permit profound statistical testing. QCA enables researchers to filter those variables or combinations of variables that empirically result in (and possibly explain) a certain outcome. As such, the method can also be used to analyze the impact of social networks on companies' innovation performance and promises valuable new insights in the field.
Innovative Comparative Methods for Policy Analysis aims to provide a decisive push to the further development and application of innovative and specific comparative methods for the improvement of policy analysis. To take on this challenge, this volume brings together methodologists and specialists from a broad range of social scientific disciplines and policy fields. The work further develops methods for systematic comparative cases analysis in a small-N research design, with a key emphasis laid on policy-oriented applications. Innovative Comparative Methods for Policy Analysis is clearly both a social scientific and policy-driven endeavor; on the one hand, the book engages in an effort to further improve social scientific methods, but on the other hand this effort also intends to provide useful, applied tools for policy analysts and the "policy community" alike. Though quite a variety of methods and techniques are touched upon in this volume, its focus is mainly laid on two recently developed research methods/techniques which enable researchers to systematically compare a limited number of cases; Qualitative Comparative Analysis(QCA) and Fuzzy-Sets (FS).
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.
Mixed Methods Research and Culture-Specific Interventions shows practicing social scientists and graduate students how to account for cultural factors when developing and evaluating psychological and educational interventions using mixed methods research. Providing a methodological basis for handling cultural influences when engaged in intervention and/or evaluation work, the book covers a range of topics, including mixed methods research, program evaluation, ethnography, and intervention design. Throughout the book, authors Bonnie K. Nastasi and John H. Hitchcock integrate illustrative examples to make more abstract content accessible. Mixed Methods Research and Culture-Specific Interventions is Volume 2 in the SAGE Mixed Methods Research Series.
Offering a variety of innovative methods and tools, The Oxford Handbook of Multimethod and Mixed Methods Research Inquiry provides the most comprehensive and up-to-date presentation on multi- and mixed-methods research available. Written in clear and concise language by leading scholars in the field, it enhances and disrupts traditional ways of asking and addressing complex research questions. Topics include an overview of theory, paradigms, and scientific inquiry; a guide to conducting a multi- and mixed-methods research study from start to finish; current uses of multi- and mixed-methods research across academic disciplines and research fields; the latest technologies and how they can be incorporated into study design; and a presentation of multiple perspectives on the key remaining debates. Each chapter in the volume is structured to include state-of-the-art research examples that cross a range of disciplines and interdisciplinary research settings. In addition, the Handbook offers multiple quantitative and qualitative theoretical and interdisciplinary visions and praxis. Researchers, faculty, graduate students, and policy makers will appreciate the exceptional, timely, and critical coverage in this Handbook, which deftly addresses the interdisciplinary and complex questions that a diverse set of research communities are facing today.
Finally, a practical guide to mixed methods research has been written with health and human services professionals in mind. Watkins and Gioia review the fundamentals of mixed methods research designs and the general suppositions of mixed methods procedures, look critically at mixed method studies and models that have already been employed in social work, and reflect on the contributions of this work to the field. But what is most important is that they lead the reader through considerations for the application of the mixed methods research in social work settings. The chapters of this book are structured so that readers can (figuratively) walk through the mixed methods research process using nine steps. Chapters one, five, and six provide supplemental material meant to serve as grounding for chapters two, three, and four, which outline nine steps in the mixed methods research process, and specific to social work research. This is a short and practical guide not just for learning about mixed methods research, but also doing it.
Integrating Analyses in Mixed Methods Research goes beyond mixed methods research design and data collection, providing a pragmatic discussion of the challenges of effectively integrating data to facilitate a more comprehensive and rigorous level of analysis. Showcasing a range of strategies for integrating different sources and forms of data as well as different approaches in analysis, it helps you plan, conduct, and disseminate complex analyses with confidence. Key techniques include: Building an integrative framework Analysing sequential, complementary and comparative data Identifying patterns and contrasts in linked data Categorizing, counting, and blending mixed data Managing dissonance and divergence Transforming analysis into warranted assertions With clear steps that can be tailored to any project, this book is perfect for students and researchers undertaking their own mixed methods research.