We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
On fitting generalized linear mixed-effects models for binary responses using different statistical packages.
- Authors
Zhang, Hui; Lu, Naiji; Feng, Changyong; Thurston, Sally W.; Xia, Yinglin; Zhu, Liang; Tu, Xin M.
- Abstract
The generalized linear mixed-effects model (GLMM) is a popular paradigm to extend models for cross-sectional data to a longitudinal setting. When applied to modeling binary responses, different software packages and even different procedures within a package may give quite different results. In this report, we describe the statistical approaches that underlie these different procedures and discuss their strengths and weaknesses when applied to fit correlated binary responses. We then illustrate these considerations by applying these procedures implemented in some popular software packages to simulated and real study data. Our simulation results indicate a lack of reliability for most of the procedures considered, which carries significant implications for applying such popular software packages in practice.
- Subjects
TREATMENT of respiratory diseases; COMPUTER software; COMPUTER simulation; LONGITUDINAL method; REGRESSION analysis; RESEARCH evaluation; RESEARCH funding; STATISTICS; DATA analysis; CROSS-sectional method; STANDARDS
- Publication
Statistics in Medicine, 2011, Vol 30, Issue 20, p2562
- ISSN
0277-6715
- Publication type
journal article
- DOI
10.1002/sim.4265