Highly Efficient Aggregate Unbiased Estimating Functions Approach for Correlated Data With Missing at Random
随机缺失相关数据的高效聚合无偏估计函数方法
We develop a consistent and highly efficient marginal model for missing at random data using an estimating function approach. Our approach differs from inverse weighted estimating equations (Robins, Rotnitzky, and Zhao 1995) and the imputation method (Paik 1997) in that our approach does not require estimating the probability of missing or imputing the missing response based on assumed models. The proposed method is based on an aggregate unbiased estimating function…