Sample size and power calculations based on generalized linear mixed models with correlated binary outcomes.

Full Abstract

The generalized linear mixed model (GLIMMIX) provides a powerful technique to model correlated outcomes with different types of distributions. The model can now be easily implemented with SAS PROC GLIMMIX in version 9.1. For binary outcomes, linearization methods of penalized quasi-likelihood (PQL) or marginal quasi-likelihood (MQL) provide relatively accurate variance estimates for fixed effects. Using GLIMMIX based on these linearization methods, we derived formulas for power and sample size calculations for longitudinal designs with attrition over time. We found that the power and sample size estimates depend on the within-subject correlation and the size of random effects. In this article, we present tables of minimum sample sizes commonly used to test hypotheses for longitudinal studies. A simulation study was used to compare the results. We also provide a Web link to the SAS macro that we developed to compute power and sample sizes for correlated binary outcomes.

Learn Faster Today Improve your study skills

Author information

Author/s: Dang, Qianyu (Q); Mazumdar, Sati (S); Houck, Patricia R (PR);

Affiliation: Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA. dangq@upmc.edu

Grants: P30 MH 71944 (Agency:United States NIMH)

Journal and publication information

Publication Type: Journal Article; Research Support, N.I.H., Extramural

Journal: Computer methods and programs in biomedicine (Comput Methods Programs Biomed), published in Ireland. (Language: eng)

Reference: 2008-Aug; vol 91 (issue 2) : pp 122-7

Dates: Created 2008/06/16; Completed 2008/09/17;

PMID: 18462826, status: MEDLINE (last retrieval date: 11/6/2008)

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.

MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Linear Models
Logistic Models
Models, Biological
Outcome Assessment (Health Care) - methods
Sample Size

These are the highest related articles currently in the database:

See 100+ related articles.