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Propensity Score Analysis: Statistical Methods and Applications (Advanced Quantitative Techniques in the Social Sciences)
by:Shenyang Y. Guo, Mark W. Fraser
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...
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 FeaturesPresents key information on model derivationsSummarizes complex statistical arguments but omits their proofsLinks each method found in this book to specific Stata programs and provides empirical examplesGuides readers using two conceptual frameworks: the Neyman-Rubin counterfactual framework and the Heckman econometric model of causalityContains examples representing real challenges commonly found in social behavioral researchUtilizes data simulation and Monte Carlo studies to illustrate key pointsPresents descriptions of new statistical approaches necessary for understanding the four evaluation methods incorporated throughout the textIntended 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.
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