A modified pseudolikelihood approach for analysis of longitudinal data.

Full Abstract

We consider the analysis of longitudinal data when the covariance function is modeled by additional parameters to the mean parameters. In general, inconsistent estimators of the covariance (variance/correlation) parameters will be produced when the "working" correlation matrix is misspecified, which may result in great loss of efficiency of the mean parameter estimators (albeit the consistency is preserved). We consider using different "working" correlation models for the variance and the mean parameters. In particular, we find that an independence working model should be used for estimating the variance parameters to ensure their consistency in case the correlation structure is misspecified. The designated "working" correlation matrices should be used for estimating the mean and the correlation parameters to attain high efficiency for estimating the mean parameters. Simulation studies indicate that the proposed algorithm performs very well. We also applied different estimation procedures to a data set from a clinical trial for illustration.

Author information

Author/s: Wang, You-Gan (YG); Zhao, Yuning (Y);

Affiliation: CSIRO Mathematical and Information Sciences, CSIRO Long Pocket Laboratories, 120 Meiers Road, Indooroopilly, Queensland 4068, Australia. You-Gan.Wang(-atsign-)csiro.acu

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Biometrics (Biometrics), published in United States. (Language: eng)

Reference: 2007-Sep; vol 63 (issue 3) : pp 681-9

Dates: Created 2007/09/10; Completed 2007/10/19; Revised 2007/11/15;

PMID: 17825002, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

External Links for this article
(including full text providers, if available):

Click Electronic Full-text Provider Links to see options for finding the electronic full text links to this article. Note there may be a subscription or fee required for access to the full text. See our FAQ for information on finding FREE full text articles.

This article may also be located in paper journal collections available in many libraries. Use the Journal and Publication Information above to find the full article.