The Role of Sampling Weights When Modeling Survey Data

Key takeaways

(file:///C:\Users\scott\Zotero\storage\X5HW8TS3\Pfeffermann%20-%201993%20-%20The%20Role%20of%20Sampling%20Weights%20When%20Modeling%20Survey%20.pdf)

Bibliography: Pfeffermann, D., 1993. The Role of Sampling Weights When Modeling Survey Data. International Statistical Review / Revue Internationale de Statistique 61, 317. https://doi.org/10.2307/1403631

Authors:: Danny Pfeffermann

Collections:: PhD

First-page: 317

Abstract

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 approaches attempt to incorporate the weights into the model.

Citations

content: "@pfeffermannRoleSamplingWeights1993" -file:@pfeffermannRoleSamplingWeights1993

Reading notes

Imported on 2024-12-07 13:30

⭐ Important

& Sampling weights weigh sample data to correct for the disproportionality of the sample with respect to the target population of (p. 317)
& ecommended. Yet, for analytical inference about model parameters, there is a wide spectrum of opinions on the role of the sampling weights, from modelers who view the weights as largely irrelevant to survey statisticians who incorporate the weights into ev (p. 317)