The Role of Sampling Weights When Modeling Survey Data
The Role of Sampling Weights When Modeling Survey Data
Key takeaways
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:
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.
content: "@pfeffermannRoleSamplingWeights1993" -file:@pfeffermannRoleSamplingWeights1993
Reading notes
Sampling weights way sample data to correct for the disproportionality of the sample with respect to the target population of interest.
Yet for analytical influence about model parameters, there is a wide spectrum of opinions on the role of sampling weights from modellers who view the weights as largely irrelevant to service statisticians who incorporate the weights into every analysis.