Combining cohorts in longitudinal surveys

Abstract

A question that commonly arises in longitudinal surveys is the issue of how to combine differing cohorts of the survey. In this paper we present a novel method for combining different cohorts, and using all available data, in a longitudinal survey to estimate parameters of a semiparametric model, which relates the response variable to a set of covariates. The procedure builds upon the Weighted Generalized Estimation Equation method for handling missing waves in longitudinal studies. Our method is set up under a joint-randomization framework for estimation of model parameters, which
takes into account the superpopulation model as well as the survey design randomization. We also propose a design-based, and a joint randomization, variance estimation method. To illustrate the methodology we apply it to the Survey of Doctorate Recipients, conducted by the U.S. National Science Foundation.