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.
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.
作者
Donglin Guo
Liugen Xue
Haiqing Chen
Donglin Guo;Liugen Xue;Haiqing Chen(College of Applied Sciences, Beijing University of Technology, Beijing, China;School of Mathematics and Information Science, Shangqiu Normal University, Shangqiu, China)
