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January 2018 Evaluating Likelihood Estimation Methods in Multilevel Analysis of Clustered Survey Data
Adeniyi Francis FAGBAMIGBE, Babatunde Bowale BAKRE
Afr. J. Appl. Stat. 5(1): 351-376 (January 2018). DOI: 10.16929/ajas/351.220

Abstract

Public health researchers often lay little or no emphasis on multilevel structure of clustered data and its likelihood estimation techniques. This has led to improper inferences. The aim of this research is to evaluate traditional methods and the different multilevel likelihood estimation procedures so as to compare their computational efficiencies.

Les chercheurs en santé publique accordent souvent peu ou pas d'importance à la structure multi-niveau des données en grappes (clusterized) et à ses techniques d'estimation basées sur la vraisemblance. Cela peut conduire à des inférences incorrectes. Le but de cette recherche est d'évaluer les méthodes traditionnelles et les différentes procédures d'estimation de vraisemblance multiniveaux afin de comparer leur efficacité.

Citation

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Adeniyi Francis FAGBAMIGBE. Babatunde Bowale BAKRE. "Evaluating Likelihood Estimation Methods in Multilevel Analysis of Clustered Survey Data." Afr. J. Appl. Stat. 5 (1) 351 - 376, January 2018. https://doi.org/10.16929/ajas/351.220

Information

Published: January 2018
First available in Project Euclid: 16 May 2019

Digital Object Identifier: 10.16929/ajas/351.220

Subjects:
Primary: 60-07 , 62H12

Keywords: adaptive Gaussian quadrature , Akaike's information criteria , clustered survey , likelihood , modern contraception , penalized quasi likelihood

Rights: Copyright © 2018 The Statistics and Probability African Society

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Vol.5 • No. 1 • January 2018
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