A potential pitfall in control of covariates in epidemiologic studies.
H. Brenner. Epidemiology (Cambridge, Mass.), 9 (1):
68-71(Januar 1998)2498.
Zusammenfassung
Control of covariates is essential in nonexperimental epidemiologic studies. Important covariates, such as smoking or alcohol consumption, often are crudely categorized in epidemiologic analyses. In this paper, I illustrate by both hypothetical and empirical examples that control of crudely categorized covariates can yield strongly misleading results. In particular, I show that, under certain conditions, control for crudely classified covariates can even be worse than not controlling for such covariates at all. I conclude that covariate specification is an issue that requires much more care than it commonly receives in epidemiologic analyses.
%0 Journal Article
%1 Brenner1998
%A Brenner, H
%D 1998
%J Epidemiology (Cambridge, Mass.)
%K Case-ControlStudies ConfoundingFactors(Epidemiology) EffectModifier Epidemiologic EpidemiologicMethods Humans
%N 1
%P 68-71
%T A potential pitfall in control of covariates in epidemiologic studies.
%U http://www.ncbi.nlm.nih.gov/pubmed/9430271
%V 9
%X Control of covariates is essential in nonexperimental epidemiologic studies. Important covariates, such as smoking or alcohol consumption, often are crudely categorized in epidemiologic analyses. In this paper, I illustrate by both hypothetical and empirical examples that control of crudely categorized covariates can yield strongly misleading results. In particular, I show that, under certain conditions, control for crudely classified covariates can even be worse than not controlling for such covariates at all. I conclude that covariate specification is an issue that requires much more care than it commonly receives in epidemiologic analyses.
@article{Brenner1998,
abstract = {Control of covariates is essential in nonexperimental epidemiologic studies. Important covariates, such as smoking or alcohol consumption, often are crudely categorized in epidemiologic analyses. In this paper, I illustrate by both hypothetical and empirical examples that control of crudely categorized covariates can yield strongly misleading results. In particular, I show that, under certain conditions, control for crudely classified covariates can even be worse than not controlling for such covariates at all. I conclude that covariate specification is an issue that requires much more care than it commonly receives in epidemiologic analyses.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Brenner, H},
biburl = {https://www.bibsonomy.org/bibtex/2d7c841571b32fd1c3ad9fc3e3331b08d/jepcastel},
interhash = {93e9523104eabe8960ed248c59974486},
intrahash = {d7c841571b32fd1c3ad9fc3e3331b08d},
issn = {1044-3983},
journal = {Epidemiology (Cambridge, Mass.)},
keywords = {Case-ControlStudies ConfoundingFactors(Epidemiology) EffectModifier Epidemiologic EpidemiologicMethods Humans},
month = {1},
note = 2498,
number = 1,
pages = {68-71},
pmid = {9430271},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {A potential pitfall in control of covariates in epidemiologic studies.},
url = {http://www.ncbi.nlm.nih.gov/pubmed/9430271},
volume = 9,
year = 1998
}