African Journal of Applied Statistics

Evaluating Likelihood Estimation Methods in Multilevel Analysis of Clustered Survey Data

Adeniyi Francis FAGBAMIGBE and Babatunde Bowale BAKRE

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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.

Résumé

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.

Article information

Source
Afr. J. Appl. Stat., Volume 5, Number 1 (2018), 351-376.

Dates
First available in Project Euclid: 16 May 2019

Permanent link to this document
https://projecteuclid.org/euclid.ajas/1557972184

Digital Object Identifier
doi:10.16929/ajas/351.220

Subjects
Primary: 60-07 62H12: Estimation

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

Citation

FAGBAMIGBE, Adeniyi Francis; BAKRE, Babatunde Bowale. Evaluating Likelihood Estimation Methods in Multilevel Analysis of Clustered Survey Data. Afr. J. Appl. Stat. 5 (2018), no. 1, 351--376. doi:10.16929/ajas/351.220. https://projecteuclid.org/euclid.ajas/1557972184


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