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

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.

Locations

• Biostatistics and Biometrics Open Access Journal - View - PDF