Semiparametric Efficient Estimation for Incomplete Longitudinal Binary Data, With Application to Smoking Trends
不完整纵向二元数据的半参数有效估计及吸烟趋势应用
Incomplete longitudinal data often are analyzed with estimating equations for inference on a parameter from a marginal mean regression model. Generalized estimating equations, although commonly used for incomplete longitudinal data, are invalid for data that are not missing completely at random. There exists a class of inverse probability weighted estimating equations that are valid under dropouts missing at random, including an easy-to-implement but inefficient member. A…