Propensity Score Estimation with Random Forests
abstract: 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 F...
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| Format: | Doctoral Thesis |
| Language: | English |
| Published: |
2013
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| Online Access: | http://hdl.handle.net/2286/R.I.18132 |