摘要：In this article, to improve the doubly robust estimator, the nonlinear regression models with missing responses are studied. Based on the covariate balancing propensity score (CBPS), estimators for the regression coefficients and the population mean are obtained. It is proved that the proposed estimators are asymptotically normal. In simulation studies, the proposed estimators show improved performance relative to usual augmented inverse probability weighted estimators.
关键词：Nonlinear Regression Model;Missing at Random;Covariate Balancing Propensity Score;GMM;Augmented Inverse Probability Weighted
