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Abstract

In their recent book Qualitative Comparative Analysis Using R: A Beginner’s Guide, Ioana-Elena Oana, Carsten Q. Schneider, and Eva Thomann provide a step-by-step guide on how to implement the latest QCA protocol in R. Published by Cambridge University Press in 2021, the book aims to “facilitate the efficient teaching, use, and independent learning” of QCA with advanced software (Oana et al., 2021, p. 21). This book is a must-read for beginners as well as experienced scholars. Starting with the basics, it ultimately represents an excellent manual on how to apply the most recent developments in QCA using R software.
Media Review
Journal of Mixed Methods Research
2022, Vol. 0(0) 13
© The Author(s) 2022
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DOI: 10.1177/15586898221115290
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Media Review
Oana, I.-E., Schneider, C. Q., & Thomann, E. (2021). Qualitative Comparative Analysis Using R: A Beginners Guide.
Cambridge University Press.
Reviewed by: Ekaterina Paustyan,Faculty of Business Studies and Economics, University of Bremen, Bremen,
Germany
Introduction
In their recent book Qualitative Comparative Analysis Using R: A Beginners Guide, Ioana-Elena
Oana, Carsten Q. Schneider, and Eva Thomann provide a step-by-step guide on how to implement
the latest QCA protocol in R. Published by Cambridge University Press in 2021, the book aims to
facilitate the efcient teaching, use, and independent learningof QCA with advanced software
(Oana et al., 2021, p. 21). This book is a must-read for beginners as well as experienced scholars.
Starting with the basics, it ultimately represents an excellent manual on how to apply the most
recent developments in QCA using R software.
Summary of the Media Content
The book is structured into three parts that correspond to the steps of QCA before, during, and after
the analysis. Chapter 1 starts with an introduction of QCA as a research approach and its core
assumptions. It also outlines essentials of a research design for a typical QCA study. Chapter 2
focuses on the calibration process, which is highly important, given that QCA does not operate on
existing data and instead uses the membership scores of cases in sets. The authors present different
approaches to the assignment of set membership scores to cases and demonstrate major diagnostic
tools that can be used during calibration.
Chapters 3 and 4 guide the reader through the analyses of necessity and sufciency, respectively.
They rst outline the logic behind these analyses and then explain the interpretation of their pa-
rameters of t. In Chapter 3, the authors also consider two sources of trivialness for necessity and
highlight that any detected necessary conditions must be meaningful conceptually. In Chapter 4,
Oana, Schneider and Thomann provide practical advice about how to deal with model ambiguity as
well as suggest several strategies to manage the problem of limited empirical diversity.
Chapters 5 and 6 present advanced analytic tools that can be used following the main analysis
of the data. In particular, Chapter 5 outlines sophisticated ways to assess robustness of QCA
results. It also explains the cluster diagnostics and how to integrate sequences and casual chains
into QCA. Chapter 6 is devoted to set-theoretic theory evaluation as well as set-theoretic multi-
method research that allows scholars to identify typical and deviant cases for in-depth case studies.
Finally, Chapter 7 provides a more general discussion of how to interpret QCA results, presents
standards of good practice, and outlines the major developments that are likely to shape the
application of QCA in the future.
Value of the Media
The book will be denitely of interest not only for beginners but also for advanced users of QCA
and mixed methods researchers. In particular, scholars doing mixed methods research largely
benet from reading Chapter 6 because it focuses on how to bring cases back into the picture after
a QCA result has been produced(Oana et al., 2021, p. 180). The authors explicitly point out that
by studying individual cases researchers are able to make their QCA-based inferences stronger as
well as to identify specic mechanisms linking sufcient combinations of conditions to the
outcome. In Chapter 6, Oana, Schneider and Thomann also discuss how to select best available
cases for within-case analysis depending on distinctive analytical goals.
Contribution to Literature and Minor Criticisms
Overall, the book successfully reaches its objective to introduce a new method and new software.
Each chapter contains numerous empirical examples and illustrations that help the reader to grasp
the main concepts presented by the authors. In addition, each chapter includes executable R code
with a detailed explanation. Following this step-by-step guide, readers will be able to implement
not only the up-to-date QCA protocol but also various ways of visualizing QCA results and to
perform such advanced diagnostics as robustness checks, set-theoretic theory evaluation and set-
theoretic multi-method research.
This book also makes a signicant contribution to the literature promoting transparency and
replicability in qualitative and mixed methods research. The authors provide explicit guidance
regarding how to establish the highest possible levels of transparency about the analysisso the
results are replicable and traceable by readers (Oana et al., 2021, p. 219). Furthermore, the
analyses in the book are done in a transparent way. All materials including data sets, R scripts,
template R code are freely available online. These resources will be very helpful for both learning
and teaching QCA.
However, since QCA is still an emerging methodology, the book might have beneted from a
section discussing more general debates about strengths and limitations of QCA as a research
approach and a technique to address doubts and concerns that novice users might have regarding
this method. In addition, while the authors provide extensive number of good empirical examples
to facilitate the learning process, examples of not so good applications of QCA could have been
also informative and educating.
Conclusion
All in all, Qualitative Comparative Analysis Using R: A Beginners Guide offers a gentle in-
troduction to QCA using R software. Starting with the basics, the authors eventually provide an
overview of the most advanced developments in QCA and explain how to apply them in R. This
book is an essential reading for a wide audience including teachers, students, as well as prac-
titioners and researchers interested in case-based methodology and mixed methods research.
2Journal of Mixed Methods Research 0(0)
Acknowledgments
I would like to thank Dr. Tyler G. James for extending the invitation to review the book.
ORCID iD
Ekaterina Paustyan https://orcid.org/0000-0002-4646-0550
Reference
Oana, I.-E., Schneider, C. Q., & Thomann, E. (2021). Qualitative comparative analysis using R: A Beginners
guide. Cambridge University Press.
Paustyan 3
Book
A comprehensive introduction and teaching resource for state-of-the-art Qualitative Comparative Analysis (QCA) using R software. This guide facilitates the efficient teaching, independent learning, and use of QCA with the best available software, reducing the time and effort required when encountering not just the logic of a new method, but also new software. With its applied and practical focus, the book offers a genuinely simple and intuitive resource for implementing the most complete protocol of QCA. To make the lives of students, teachers, researchers, and practitioners as easy as possible, the book includes learning goals, core points, empirical examples, and tips for good practices. The freely available online material provides a rich body of additional resources to aid users in their learning process. Beyond performing core analyses with the R package QCA, the book also facilitates a close integration with the R package SetMethods allowing for a host of additional protocols for building a more solid and well-rounded QCA.