psychometrika—vol. 83, no. 1, 275–278
REVIEW OF PRACTICAL PROPENSITY SCORE METHODS USING R (LEITE, 2007)
LEITE, W (2017). Practical Propensity Score Methods Using R. Thousand Oaks, CA: Sage
Publications, p. 224, $50.00. ISBN: 978-1-4522-8888-8.
How to make causal inference from quasi-experimental designs or observational studies is a
key issue in social and behavioral research as well as many other ﬁelds. Propensity score methods
(PSMs) (Rosenbaum & Rubin, 1983) have become popular techniques for reducing selection
bias in an attempt to improve the validity of research for causal inference. In addition to many
journal articles and tutorial workshops on propensity score methods, the recently published book,
Practical Propensity Score Methods Using R (Leite, 2017), is a good and timely tool for promoting
the practical use of PSMs in observational studies.
1. What is the Book About?
Complementary to existing books on PSMs which are more theoretically based (e.g.,
GuoFraser, 2014; Pan & Bai, 2015), Leite’s book provides a practical guide for researchers and
graduate students in the social and behavioral sciences on how to implement PSMs using the R
software. The timing of the book is impeccable because it has become increasingly popular to use
PSMs in observational studies. Although the literature contains a few tutorials on propensity score
methods (e.g., Austin, 2011; Caliendo & Kopeinig, 2008), no book has primarily focused on pro-
viding a systematic and fundamental guide to PSMs with speciﬁc statistical software. The content
of this book is comprehensive from basic techniques (matching, stratiﬁcation, and weighting) to
advanced PSM applications related to speciﬁc designs and treatment effect estimations (contin-
uous treatments, sensitivity analysis, and complex data including latent variables, longitudinal,
and multilevel data). The readers will beneﬁt from the book’s step-by-step tutorial approach to
applying PSMs using the popular and powerful R software with real-world examples.
2. Who is the Primary Audience?
This book is written for readers with a basic knowledge of statistics, who need to learn how
to implement PSMs using R. The book can be adopted as a core or supplemental textbook for
research design courses, and it can also be used as a reference book for empirical researchers who
use advanced quantitative research methods. The pedagogy of the book is systematic and easy
to follow. Each chapter begins with learning objectives, followed by a real-world example, and
ends with study questions. The treatment of the book’s content is particularly helpful for graduate
students and novice users of PSMs. This book also provides a hyperlink to a website where readers
will ﬁnd free online resources of R codes and sample data so that readers can practice and replicate
examples in the book.
© 2017 The Psychometric Society