  Modeling correlated or highly stratified multiple-response data becomes a
common data analysis task due to modern data monitoring facilities and methods.
Generalized estimating equations (GEE) is one of the popular statistical
methods for analyzing this kind of data. In this paper, we present a sequential
estimation procedure for obtaining GEE-based estimates. In addition to the
conventional random sampling, the proposed method features adaptive subject
recruiting and variable selection. Moreover, we equip our method with an
adaptive shrinkage property so that it can decide the effective variables
during the estimation procedure and build a confidence set with a pre-specified
precision for the corresponding parameters. In addition to the statistical
properties of the proposed procedure, we assess our method using both simulated
data and real data sets.
