Propensity Score Methods and Applications by Bai, Haiyan

Propensity Score Methods and Applications

A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they...
HK$557.69
HK$557.69
SKU: 9781506378053
Product Type: Books
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Author: Haiyan Bai
Format: Paperback
Language: English
Subtotal: $557.69
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Propensity Score Methods and Applications by Bai, Haiyan

Propensity Score Methods and Applications

$557.69

Propensity Score Methods and Applications

$557.69
Author: Haiyan Bai
Format: Paperback
Language: English
A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method.

Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own.

Author: Haiyan Bai, M. H. Clark
Publisher: Sage Publications, Inc
Published: 12/13/2018
Pages: 136
Binding Type: Paperback
Weight: 0.35lbs
Size: 8.30h x 5.50w x 0.30d
ISBN: 9781506378053

About the Author
Bai, Haiyan: -

Dr. Haiyan Bai is a Professor at the University of Central Florida. She earned her Ph.D. in quantitative research methodology at the University of Cincinnati. Her research interests include issues that revolve around statistical/quantitative methods, specifically, propensity score methods, resampling techniques, research design, measurement, and the application of statistical methods in social and behavioral sciences.


Clark, M. H.: -

Dr. M. H. Clark is an Associate Lecturer, statistical consultant, and program evaluator at the University of Central Florida. She has a Ph.D. in Experimental Psychology with a specialization in research design and statistics from the University of Memphis. Her specific areas of expertise are in causal inference, selection bias in non-randomized experiments, and propensity score methods.




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