Statistical Methods in Medical Research

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Sign In to gain access to subscriptions and/or personal tools.
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Neuhaus, J. M
Right arrow Search for Related Content
PubMed
Right arrow Articles by Neuhaus, J. M
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Statistical Methods in Medical Research, Vol. 1, No. 3, 249-273 (1992)
DOI: 10.1177/096228029200100303

Statistical methods for longitudinal and clustered designs with binary responses

John M Neuhaus

Department of Epidemiology and Biostatistics, University of California

Dependent binary response data arise frequently in practice due to repeated measurements in longitudi nal studies or to subsampling primary sampling units as in fields such as teratology and ophthalmology. Several classes of approaches have recently been proposed to analyse such repeated binary outcome data. The different classes of approaches measure different effects of covariates on binary responses and address different statistical questions. This article compares the different classes of approaches in terms of parameter interpretation and magnitude, standard errors of model parameters and Wald tests for covariate effects. The results help to clarify the substantive questions which data analysts can address with each approach, as well as why the covariate effects measured by different approaches may be different. Finally, I will provide guidelines to the advantages and disadvantages of alternative approaches for analysing dependent binary responses. Simulations and example data illustrate these findings.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
GerontologistHome page
C. E. Bishop, D. B. Weinberg, W. Leutz, A. Dossa, S. G. Pfefferle, and R. M. Zincavage
Nursing Assistants' Job Commitment: Effect of Nursing Home Organizational Factors and Impact on Resident Well-Being
Gerontologist, July 1, 2008; 48(suppl_1): 36 - 45.
[Abstract] [Full Text] [PDF]


Home page
Appl. Environ. Microbiol.Home page
N. H. Ogden, L. R. Lindsay, K. Hanincova, I. K. Barker, M. Bigras-Poulin, D. F. Charron, A. Heagy, C. M. Francis, C. J. O'Callaghan, I. Schwartz, et al.
Role of Migratory Birds in Introduction and Range Expansion of Ixodes scapularis Ticks and of Borrelia burgdorferi and Anaplasma phagocytophilum in Canada
Appl. Envir. Microbiol., March 15, 2008; 74(6): 1780 - 1790.
[Abstract] [Full Text] [PDF]