Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8057

Title: A family of tests to detect misspecifications in the random-effects structure of generalized linear mixed models
Authors: Alonso Abad, Ariel
Litière, Saskia
Molenberghs, Geert
Issue Date: 2008
Publisher: Elsevier
Abstract: Estimation in generalized linear mixed models for non-Gaussian longitudinal data is often based on maximum likelihood theory, which assumes that the underlying probability model is correctly specified. It is known that the results obtained from these models are not always robust against misspecification of the random-effects structure. Therefore, diagnostic tools for the detection of this misspecification are of the utmost importance. Three diagnostic tests, based on the eigenvalues of the variance-covariance matrices for the fixed-effects parameters estimates, are proposed in the present work. The power and type I error rate of these tests are studied via simulations. A very acceptable performance was observed in many cases, especially for those misspecifications that can have a big impact on the maximum likelihood estimators.
URI: http://hdl.handle.net/1942/8057
DOI: 10.1016/j.csda.2008.02.033
ISI #: 000257014000022
ISSN: 0167-9473
Category: A1
Type: Journal Contribution
Validation: ecoom, 2009
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
Published version381.41 kBAdobe PDF
Peer-reviewed author version461.35 kBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.