Abstract #301273

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JSM 2003 Abstract #301273
Activity Number: 67
Type: Invited
Date/Time: Monday, August 4, 2003 : 8:30 AM to 10:20 AM
Sponsor: Journal of Agricultural, Biological and Environmental Stats (JABES)
Abstract - #301273
Title: Recent Advances in Analysis of Unbalanced Mixed Model Data
Author(s): Ramon C. Littell*+ and Jamie M. Baldwin
Companies: University of Florida and University of Florida
Address: 524 McCarty-C, Gainesville, FL, 32611-0339,
Keywords: likelihood ; mixed models ; generalized least squares ; approximations
Abstract:

In recent years, statisticians engaged in analysis of mixed model data have turned toward likelihood-based methods based on models that incorporate random effects. In most cases, the objective is to make inference about fixed effects in the model. The likelihood-based mixed model methods first require estimation of the random effect parameters, for which REML is usually used. Then those estimates are substituted into the covariance matrix to obtain (approximate) generalized least squares inference pertaining to fixed effects. The entire process results in several layers of approximation involving variances, standard errors of estimates, and degrees of freedom. Some of the approximations are implemented into computer programs, and users are not always sure of the impact of the approximations. This paper summarizes recent research on the topic and attempts to describe situations in which the approximations are troublesome or not.

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