Statistical Science

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
https://projecteuclid.org/euclid.ss/1494489809

Digital Object Identifier
doi:10.1214/17-STS614

Mathematical Reviews number (MathSciNet)
MR3648953

Zentralblatt MATH identifier
1381.62031

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. https://projecteuclid.org/euclid.ss/1494489809


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