Propensity Score Analysis
FUNDAMENTALS AND DEVELOPMENTS
Edited by Wei Pan and Haiyan Bai
Published by The Guilford Press in April 2015
To the contributing authors
for their remarkable cooperation
and commitment to the advancement
of propensity score methodology
Since Donald B. Rubin and Paul R. Rosenbaum's seminal work on causal inference and propensity score analysis in the late 70s and early 80s, propensity score analysis has become increasingly popular in the social, behavioral, and health sciences for making causal inferences from observational studies. However, both methodological and practical challenges persist in the use of propensity score analysis. This edited book introduces new developments that address the challenges and, hopefully, stimulates more discussions and, therefore, advances its use in the social, behavioral, and health sciences.
"Pan and Bai have assembled a comprehensive volume on all aspects of propensity score methods. Both the user and the statistician will find something to like in this book. I recommend it. "
-William R. Shadish, Ph.D. (1949-2016),
Late Distinguished Professor of Psychology, University of California, Merced
"There is no question that this book will serve as an excellent resource for those who want to add PSA to their repertoire of analytical methods. The chapters provide sufficient materials and examples to help both 'green hands' and seasoned analysts deal with the methodological and practical challenges of applying PSA in research work."
-Xitao Fan, Ph.D.,
Wei Lun Professor and Dean, Faculty of Education, The Chinese University of Hong Kong, China
"This book effectively synthesizes general principles of PSA with recent developments regarding complex issues such as estimation techniques, covariate balance, weighting, complex datasets, and sensitivity analysis. The discussion of statistical software and examples of computer code are helpful additions. This book will be useful to graduate students and applied researchers who are interested in learning about PSA for the first time or who have some knowledge and would like to learn about issues and recent developments. I recommend it as a textbook for graduate-level courses in methods of causal inference or as a reference for researchers in the social and biomedical sciences."
-Suzanne E. Graham, Ed.D.,
Associate Professor, Department of Education, University of New Hampshire
"This book is a go-to guide for designing and analyzing observational data. The editors have produced a brilliant work that addresses both methodological and practical issues in propensity score analysis. A 'must read' for all biostatisticians as well as applied researchers in the social, behavioral, and health sciences."
-Ding-Geng (Din) Chen, Ph.D.,
Professor, College of Health Solutions, Arizona State University