Statistical Science
- Statist. Sci.
- Volume 32, Number 2 (2017), 165-175.
Introduction to the Design and Analysis of Complex Survey Data
Chris Skinner and Jon Wakefield
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Abstract
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.
Article information
Source
Statist. Sci. Volume 32, Number 2 (2017), 165-175.
Dates
First available in Project Euclid: 11 May 2017
Permanent link to this document
http://projecteuclid.org/euclid.ss/1494489809
Digital Object Identifier
doi:10.1214/17-STS614
Keywords
Design-based inference model-assisted inference model-based inference weights variance estimation
Citation
Skinner, Chris; Wakefield, Jon. Introduction to the Design and Analysis of Complex Survey Data. Statist. Sci. 32 (2017), no. 2, 165--175. doi:10.1214/17-STS614. http://projecteuclid.org/euclid.ss/1494489809.
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