Some Statistical Considerations in the Analysis of Case‐Control Studies When the Exposure Variables Are Continuous Measurements
作者:
Chris Robertson,
Peter Boyle,
Chung-cheng Hsieh,
Gary Macfarlane,
Patrick Maisonneuve,
期刊:
Epidemiology
(OVID Available online 1994)
卷期:
Volume 5,
issue 2
页码: 164-170
ISSN:1044-3983
年代: 1994
出版商: OVID
关键词: logistic regression;differential variability;nonexposure;dose-response;case-control studies;models;confounding;data analysis.
数据来源: OVID
摘要:
This paper focuses on some statistical considerations in the estimation of dose-response in case-control studies when the exposure variables are continuous measurements. The first point is that the effects of differential variability in the exposure distributions over cases and controls cannot be differentiated from a true quadratic risk model. The second point is that when dealing with variables where zero denotes no exposure, it is important to treat the unexposed subjects separately from those who were exposed. Failure to do so can lead to differential variability among cases and controls and the resulting confounding with a quadratic risk model. Both of these points are illustrated by an example.
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