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Propensity Score Methods and Applications
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Propensity Score Methods and Applications

December 2018 | 136 pages | SAGE Publications, Inc
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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.

 
Series Editor’s Introduction
 
About the Authors
 
Acknowledgments
 
1. Basic Concepts of Propensity Score Methods
1.1 Causal Inference

 
1.2 Propensity Scores

 
1.3 Assumptions

 
1.4 Summary of the Chapter

 
 
2. Covariate Selection and Propensity Score Estimation
2.1 Covariate Selection

 
2.2 Propensity Score Estimation

 
2.3 Summary of the Chapter

 
2.4 An Example

 
 
3. Propensity Score Adjustment Methods
3.1 Propensity Score Matching

 
3.2 Other Propensity Score Adjustment Methods

 
3.3 Summary of the Chapter

 
3.4 An Example

 
 
4. Covariate Evaluation and Causal Effect Estimation
4.1 Evaluating the Balance of Covariate Distributions

 
4.2 Causal Effect Estimation

 
4.3 Sensitivity Analysis

 
4.4 Summary of the Chapter

 
4.5 An Example

 
 
5. Conclusion
5.1 Limitations of the Propensity Score Methods and How to Address Them

 
5.2 Summary of Propensity Score Procedures

 
5.3 Final Comments

 
 
References
 
Index
Key features

KEY FEATURES: 

  • Written for substantive researchers rather than statisticians, the authors introduce the basic concepts of propensity score methods (PSM) using concise, plain language.
  • A FREE companion website includes statistical code, output, and interpretations for several statistical packages, allowing researchers to practice implementing PSM.
  • Clear, distinctive steps throughout the text instruct readers on how they can effectively apply PSM to their own studies.
  • Researchers are able to make modifications to analyses depending on data-specific conditions and the book provides helpful guidelines for which procedures are most appropriate.
  • Helpful checklists summarize when and how to use PSM, providing brief reminders of the fundamental steps in conducting PSM.
 

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