A Simple Approach for Fitting Linear Relative Rate Models in SAS
-
2008/12/01
Details
-
Personal Author:
-
Description: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). [Description provided by NIOSH]
-
Subjects:
-
Keywords:
-
ISSN:0002-9262
-
Document Type:
-
Funding:
-
Genre:
-
Place as Subject:
-
CIO:
-
Topic:
-
Location:
-
Volume:168
-
Issue:11
-
NIOSHTIC Number:nn:20034830
-
Citation:Am J Epidemiol 2008 Dec; 168(11):1333-1338
-
Contact Point Address:David B. Richardson, University of North Carolina at Chapel Hill, School of Public Health, CB 7435, Chapel Hill, NC 27599
-
Email:david.richardson@unc.edu
-
Federal Fiscal Year:2009
-
NORA Priority Area:
-
Performing Organization:University of North Carolina, Chapel Hill
-
Peer Reviewed:True
-
Start Date:20060701
-
Source Full Name:American Journal of Epidemiology
-
End Date:20090630
-
Collection(s):
-
Main Document Checksum:urn:sha-512:b23327a9f9c5068a4caf899b1a8db43fef46ff860e10d18977a38c49447079d5c063dd4d6ff6f58ac92150d1fc7012ed1fff8685f54f46ec7f810560bc5637dc
-
Download URL:
-
File Type:
ON THIS PAGE
CDC STACKS serves as an archival repository of CDC-published products including
scientific findings,
journal articles, guidelines, recommendations, or other public health information authored or
co-authored by CDC or funded partners.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
You May Also Like