Open Access
May 2017 Introduction to the Design and Analysis of Complex Survey Data
Chris Skinner, Jon Wakefield
Statist. Sci. 32(2): 165-175 (May 2017). DOI: 10.1214/17-STS614


We give a brief overview of common sampling designs used in a survey setting, and introduce the principal inferential paradigms under which data from complex surveys may be analyzed. In particular, we distinguish between design-based, model-based and model-assisted approaches. Simple examples highlight the key differences between the approaches. We discuss the interplay between inferential approaches and targets of inference and the important issue of variance estimation.


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Chris Skinner. Jon Wakefield. "Introduction to the Design and Analysis of Complex Survey Data." Statist. Sci. 32 (2) 165 - 175, May 2017.


Published: May 2017
First available in Project Euclid: 11 May 2017

zbMATH: 1381.62031
MathSciNet: MR3648953
Digital Object Identifier: 10.1214/17-STS614

Keywords: design-based inference , model-assisted inference , model-based inference , variance estimation , weights‎

Rights: Copyright © 2017 Institute of Mathematical Statistics

Vol.32 • No. 2 • May 2017
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