Random Forests is a statistical learning method which has been proposed for propensity score estimation models that involve complex interactions, nonlinear relationships, or both of the covariates. In this dissertation I conducted a simulation study to examine the effects of three Random Forests model specifications in propensity score analysis.
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- Partial requirement for: Ph. D., Arizona State University, 2013Note typethesis
- Includes bibliographical references (p. 77-81)Note typebibliography
- Field of study: Psychology