Pages that link to "Item:Q2325020"
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The following pages link to Propensity score estimation using classification and regression trees in the presence of missing covariate data (Q2325020):
Displaying 6 items.
- Should we impute or should we weight? Examining the performance of two CART-based techniques for addressing missing data in small sample research with nonnormal variables (Q1658370) (← links)
- Extending balance assessment for the generalized propensity score under multiple imputation (Q2197496) (← links)
- Adjustment for Missing Confounders Using External Validation Data and Propensity Scores (Q4916437) (← links)
- Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data (Q5222225) (← links)
- Coarsened Propensity Scores and Hybrid Estimators for Missing Data and Causal Inference (Q6064617) (← links)
- A latent class model to multiply impute missing treatment indicators in observational studies when inferences of the treatment effect are made using propensity score matching (Q6141305) (← links)
