Average Reviews:
(More customer reviews)I am a fourth year PhD student at University of Toronto and this textbook has been a very useful source on estimating treatment effects as part of my research.
I think it is particularly good at (1) explaining the differences between Heckman-type selection models and matching models; and at (2) summarizing different matching approaches including propensity score, matching estimators, and non-parametric techniques. Moreover, it provides details on how to perform sensitivity analysis and perform diagnostics for each technique. I liked that each chapter explains briefly the theoretical foundations of every approach and provides detailed guidance using examples on how to run STATA or R code.
Click Here to see more reviews about: Propensity Score Analysis: Statistical Methods and Applications (Advanced Quantitative Techniques in the Social Sciences)
Propensity Score Analysis provides readers with a systematic review of the origins, history, and statistical foundations of PSA and illustrates how it can be used for solving evaluation problems. With a strong focus on practical applications, the authors explore various types of data and evaluation problems related to, strategies for employing, and the limitations of PSA. Unlike the existing textbooks on program evaluation, Propensity Score Analysis delves into statistical concepts, formulas, and models underlying the application.Key Features
Presents key information on model derivations
Summarizes complex statistical arguments but omits their proofs
Links each method found in this book to specific Stata programs and provides empirical examples
Guides readers using two conceptual frameworks: the Neyman-Rubin counterfactual framework and the Heckman econometric model of causality
Contains examples representing real challenges commonly found in social behavioral research
Utilizes data simulation and Monte Carlo studies to illustrate key points
Presents descriptions of new statistical approaches necessary for understanding the four evaluation methods incorporated throughout the text
Intended AudienceThis text is appropriate for graduate and doctoral students taking Evaluation, Quantitative Methods, Survey Research, and Research Design courses across business, social work, public policy, psychology, sociology, and health/medicine disciplines.
