Random measurement error and regression dilution bias.

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State: Public
Version: author
Serval ID
serval:BIB_7DFB09EAC90A
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Random measurement error and regression dilution bias.
Journal
BMJ
Author(s)
Hutcheon Jennifer A., Chiolero Arnaud, Hanley James A.
ISSN
1468-5833[electronic], 0959-535X[linking]
Publication state
Published
Issued date
2010
Volume
340
Pages
c2289
Language
english
Abstract
Summary points:
- The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease)
- Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null
- Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant
- Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable
Keywords
Bias (Epidemiology), Regression Analysis, Research, Risk Factors
Pubmed
Web of science
Create date
19/01/2011 11:16
Last modification date
20/08/2019 14:39
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