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- Title
Propensity score estimation with boosted regression for evaluating causal effects in observational studies.
- Authors
McCaffrey, Daniel F; Ridgeway, Greg; Morral, Andrew R
- Abstract
Causal effect modeling with naturalistic rather than experimental data is challenging. In observational studies participants in different treatment conditions may also differ on pretreatment characteristics that influence outcomes. Propensity score methods can theoretically eliminate these confounds for all observed covariates, but accurate estimation of propensity scores is impeded by large numbers of covariates, uncertain functional forms for their associations with treatment selection, and other problems. This article demonstrates that boosting, a modern statistical technique, can overcome many of these obstacles. The authors illustrate this approach with a study of adolescent probationers in substance abuse treatment programs. Propensity score weights estimated using boosting eliminate most pretreatment group differences and substantially alter the apparent relative effects of adolescent substance abuse treatment.
- Publication
Psychological methods, 2004, Vol 9, Issue 4, p403
- ISSN
1082-989X
- Publication type
Journal Article
- DOI
10.1037/1082-989X.9.4.403