quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a viable …

quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a viable …

regression model. Asymptotic distribution theory is developed for the estimation method which enjoys the same rate of convergence …

regression of Y onto X in a subpopulation homogenous in W = w (formally a conditional linear predictor). Let b0 (w) be the … coefficient vector on X in this regression. We introduce a semiparametrically efficient estimate of the average ß0 = E [b0 (W … familiar methods of covariate adjustment used for program evaluation as well as methods of semiparametric regression (e.g., the …

Abstract Data mining and machine learning techniques such as classification and regression trees (CART) represent a … promising alternative to conventional logistic regression for propensity score estimation. Whereas incomplete data preclude the … fitting of a logistic regression on all subjects, CART is appealing in part because some implementations allow for incomplete …

oracle property. The selected variables are used to form a doubly robust regression estimator of the treatment effect. Using …