Cao, Weihua; Tsiatis, Anastasios A.; Davidian, Marie Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data. (English) Zbl 1170.62007 Biometrika 96, No. 3, 723-734 (2009). Summary: Considerable recent interest has focused on doubly robust estimators for a population mean response in the presence of incomplete data, which involve models for both the propensity score and the regression of outcome on covariates. The usual doubly robust estimator may yield severely biased inferences if neither of these models is correctly specified and can exhibit nonnegligible bias if the estimated propensity score is close to zero for some observations. We propose alternative doubly robust estimators that achieve comparable or improved performance relative to existing methods, even with some estimated propensity scores close to zero. Cited in 1 ReviewCited in 65 Documents MSC: 62D05 Sampling theory, sample surveys 62F35 Robustness and adaptive procedures (parametric inference) Keywords:causal inference; enhanced propensity score model; missing at random; no unmeasured confounders; outcome regression; simulations PDFBibTeX XMLCite \textit{W. Cao} et al., Biometrika 96, No. 3, 723--734 (2009; Zbl 1170.62007) Full Text: DOI