Skip Navigation


American Journal of Epidemiology Advance Access originally published online on October 25, 2008
American Journal of Epidemiology 2008 168(11):1333-1338; doi:10.1093/aje/kwn278
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
168/11/1333    most recent
kwn278v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Richardson, D. B.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Richardson, D. B.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

American Journal of Epidemiology © The Author 2008. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

PRACTICE OF EPIDEMIOLOGY

A Simple Approach for Fitting Linear Relative Rate Models in SAS

David B. Richardson

Correspondence to Dr. David Richardson, Department of Epidemiology, CB 7435, School of Public Health, University of North Carolina, Chapel Hill, NC 27599 (e-mail: david.richardson{at}unc.edu).

Received for publication March 27, 2008. Accepted for publication August 4, 2008.

The linear relative rate model has been employed in epidemiologic analyses of a variety of environmental and occupational exposures. In contrast to an exponential rate model, the linear relative rate model implies that the excess relative rate of disease changes in an additive fashion with exposure. The linear relative rate model may be fitted using EPICURE (HiroSoft International Corporation, Seattle, Washington), a specialized statistical software package widely used for such analyses. In this paper, the author presents a simple approach to fitting the linear relative rate model to epidemiologic data using PROC NLMIXED in the SAS statistical software package (SAS Institute Inc., Cary, North Carolina). This approach is illustrated via analyses of data from a study of mortality in a cohort of South Carolina asbestos textile workers (1940–2001).

cohort analysis; dose-response function; epidemiologic methods; linear trend; models, statistical; Poisson regression; software

Abbreviations: ICD, International Classification of Diseases


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




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.