Modelling multilevel data under complex sampling designs: An empirical likelihood approach-Reference-Cited by-同舟云学术

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Modelling multilevel data under complex sampling designs: An empirical likelihood approach

Published:2020-05 Issue: Volume:145 Page:106906
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Oǧuz-Alper Melike,Berger Yves G.^ORCID

Funder

Economic and Social Research Council, United Kingdom

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference64 articles.

1. Comparisons between conditional Poisson sampling and pareto πps sampling designs;Aires;J. Statist. Plann. Inference,2000

2. General multi-level modelling with sampling weights;Asparouhov;Commun. Stat.- Theory Methods,2006

3. Rate of convergence to asymptotic variance for the Horvitz-Thompson estimator;Berger;J. Statist. Plann. Inference,1998

4. An empirical likelihood approach under cluster sampling with missing observations;Berger;Ann. Inst. Statist. Math.,2018

5. Empirical likelihood approaches in survey sampling;Berger;Surv. Stat.,2018

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1. Sample Design for Analysis using High-Influence Probability Sampling;Journal of the Royal Statistical Society Series A: Statistics in Society;2022-10-01

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