Some Estimation Methods and Their Assessment in Multilevel Models: A Review

Yahia S El-Horbaty and Eman M Hanafy
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Yahia S El-Horbaty: Department of Mathematics, Insurance and Applied Statistics, Helwan University, Egypt
Eman M Hanafy: Department of Mathematics, Insurance and Applied Statistics, Helwan University, Egypt

Biostatistics and Biometrics Open Access Journal, 2018, vol. 5, issue 3, 69-76

Abstract: Multilevel linear regression models represent a generalization of linear models in which the regression coefficients are themselves given a model whose parameters are also estimated from the data. This paper reviews multilevel random coefficients regression models with a focus on the estimation problem and its assessment. Parameter estimation for the fixed effects and the variance components are highlighted. In addition, comparisons that are made in the literature to choose among the competing methods are highlighted. This is particularly emphasized when some of the assumptions underlying the estimation methods are violated.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:5:y:2018:i:3:p:69-76

DOI: 10.19080/BBOAJ.2018.05.555662

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