Propensity Score Analysis

1. Propensity Score Analysis: Concepts and Issues, Wei Pan & Haiyan Bai

2. Overview of Implementing Propensity Score Analysis in Statistical Software, Megan Schuler

II. Propensity Score Estimation, Matching, and Covariate Balance

3. Propensity Score Estimation with Boosted Regression, Lane F. Burgette, Daniel F. McCaffrey, & Beth Ann Griffin

4. Methodological Considerations in Implementing Propensity Score Matching, Haiyan Bai

5. Evaluating Covariate Balance, Cassandra W. Pattanayak

III. Weighting Schemes and Other Strategies for Outcome Analysis after Matching

6. Propensity Score Adjustment Methods, M. H. Clark

7. Propensity Score Analysis with Matching Weights, Liang Li, Tom H. Greene, & Brian C. Sauer

8. Robust Outcome Analysis for Propensity-Matched Designs, Scott F. Kosten, Joseph W. McKean, & Bradley E. Huitema

IV. Propensity Score Analysis on Complex Data

9. Latent Growth Modeling of Longitudinal Data with Propensity-Score-Matched Groups, Walter L. Leite

10. Propensity Score Matching on Multilevel Data, Qiu Wang

11. Propensity Score Analysis with Complex Survey Samples, Debbie L. Hahs-Vaughn

V. Sensitivity Analysis and Extensions Related to Propensity Score Analysis

12. Missing Data in Propensity Scores, Robin Mitra

13. Unobserved Confounding in Propensity Score Analysis, Rolf H. H. Groenwold & Olaf H. Klungel

14. Propensity-Score-Based Sensitivity Analysis, Lingling Li, Changyu Shen, & Xiaochun Li

15. Prognostic Scores in Clustered Settings, Ben Kelcey & Christopher M. Swoboda

Author Index

Subject Index

About the Editors

Contributors