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A simple approach for fitting linear relative rate models in SAS.

Authors
Richardson-DB
Source
Am J Epidemiol 2008 Dec; 168(11):1333-1338
NIOSHTIC No.
20034830
Abstract
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).
Keywords
Risk-factors; Risk-analysis; Occupational-diseases; Occupational-exposure; Models; Mathematical-models; Statistical-analysis; Author Keywords: cohort analysis; dose-response function; epidemiologic methods; linear trend; models; statistical; Poisson regression; software
Contact
David B. Richardson, University of North Carolina at Chapel Hill, School of Public Health, CB 7435, Chapel Hill, NC 27599
CODEN
AJEPAS
Publication Date
20081201
Document Type
Journal Article
Email Address
david.richardson@unc.edu
Funding Type
Grant
Fiscal Year
2009
NTIS Accession No.
NTIS Price
Identifying No.
Grant-Number-K01-OH-008635
Issue of Publication
11
ISSN
0002-9262
Priority Area
Manufacturing
Source Name
American Journal of Epidemiology
State
NC
Performing Organization
University of North Carolina, Chapel Hill
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