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An empirical likelihood approach for complex sampling

An empirical likelihood approach for complex sampling
An empirical likelihood approach for complex sampling
Survey data are often collected with unequal probabilities from a stratified population. We propose an empirical likelihood approach for sample data selected with unequal probabilities. We show that the empirical likelihood ratio statistic follows a chi-squared distribution asymptotically. The approach proposed does not rely on variance estimates, re-sampling or joint-inclusion probabilities, even when the parameter of interest is not linear. Standard confidence intervals based on variance estimates may give poor coverages, when normality does not hold. This can be the case with skewed data and outlying values. This paper contains the main results of Oguz-Alper & Berger (2016a,c) published by Oxford University Press. Oguz-Alper & Berger’s (2016a) empirical likelihood confidence interval has good coverages, even when the sampling distribution of the point estimator is not normal.
Berger, Yves
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Oguz Alper, Melike
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Berger, Yves
8fd6af5c-31e6-4130-8b53-90910bf2f43b
Oguz Alper, Melike
d555d994-86fa-4835-80da-c5a3b0a91bcc

Berger, Yves and Oguz Alper, Melike (2016) An empirical likelihood approach for complex sampling In Proceedings Papers of the 2016 Meeting of the Statistical Society of Canada. 9 pp.

Record type: Conference or Workshop Item (Paper)

Abstract

Survey data are often collected with unequal probabilities from a stratified population. We propose an empirical likelihood approach for sample data selected with unequal probabilities. We show that the empirical likelihood ratio statistic follows a chi-squared distribution asymptotically. The approach proposed does not rely on variance estimates, re-sampling or joint-inclusion probabilities, even when the parameter of interest is not linear. Standard confidence intervals based on variance estimates may give poor coverages, when normality does not hold. This can be the case with skewed data and outlying values. This paper contains the main results of Oguz-Alper & Berger (2016a,c) published by Oxford University Press. Oguz-Alper & Berger’s (2016a) empirical likelihood confidence interval has good coverages, even when the sampling distribution of the point estimator is not normal.

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Published date: 2016

Identifiers

Local EPrints ID: 414143
URI: http://eprints.soton.ac.uk/id/eprint/414143
PURE UUID: 95dea581-09a1-4dbc-90e3-dba54830be15

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Date deposited: 15 Sep 2017 16:30
Last modified: 15 Sep 2017 16:30

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Contributors

Author: Yves Berger
Author: Melike Oguz Alper

University divisions

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