The Role of Sampling Weights When Modeling Survey Data

TLDR

The paper surveys the literature to determine whether sampling weights can be justified for inference on model parameters and to develop guidelines for incorporating them. Six weighting strategies are examined, four of which yield design‑consistent estimators for population model parameters, while the remaining two provide alternative approaches. The study concludes that sampling weights can be used to test for informative sampling designs and to guard against model misspecification in the population.

Abstract

Summary The purpose of this paper is to provide a critical survey of the literature, directed at answering two main questions. i) Can the use of the sampling weights be justified for analytic inference about model parameters and if so, under what circumstances? ii) Can guidelines be developed for how to incorporate the weights in the analysis? The general conclusion of this study is that the weights can be used to test and protect against informative sampling designs and against misspecification of the model holding in the population. Six approaches for incorporating the weights in the inference process are considered. The first four approaches are intended to yield design consistent estimators for corresponding descriptive population quantities of the model parameters. The other two