Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 1067-1092 |
| Number of pages | 26 |
| Journal | Statistics in Medicine |
| Volume | 28 |
| Issue number | 7 |
| Early online date | 16 Feb 2009 |
| DOIs | |
| Publication status | Published - 30 Mar 2009 |
Fingerprint
Keywords
- measurement error
- within-person variation
- meta-analysis
- individual participant data
- regression calibration
Cite this
Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies. / Lee, Amanda; Fibrinogen Studies Collaboration.
In: Statistics in Medicine, Vol. 28, No. 7, 30.03.2009, p. 1067-1092.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies
AU - Lee, Amanda
AU - Fibrinogen Studies Collaboration
PY - 2009/3/30
Y1 - 2009/3/30
N2 - Within-person variability in measured values of multiple risk factors call bias their associations with disease. The multivariate regression calibration (RC) approach call correct for such measurement error and has been applied to Studies in which true Values or independent repeat measurements of the risk factors are observed oil a subsample. We extend the multivariate RC techniques to a meta-analysis framework where Multiple studies provide independent repeat measurements and information oil disease outcome. We consider the cases where sonic or all studies have repeat measurements, and compare study-specific, averaged and empirical Bayes estimates of RC parameters. Additionally, we allow for binary covariates (e.g. smoking status) and for uncertainty and time trends in the measurement error corrections. Our methods are illustrated using a subset of individual participant data from prospective long-term studies ill the Fibrinogen Studies Collaboration to assess file relationship between usual levels of plasma fibrinogen and the risk of coronary heart disease, allowing for measurement error in plasma fibrinogen and several confounders. Copyright (C) 2009 John Wiley & Soils, Ltd.
AB - Within-person variability in measured values of multiple risk factors call bias their associations with disease. The multivariate regression calibration (RC) approach call correct for such measurement error and has been applied to Studies in which true Values or independent repeat measurements of the risk factors are observed oil a subsample. We extend the multivariate RC techniques to a meta-analysis framework where Multiple studies provide independent repeat measurements and information oil disease outcome. We consider the cases where sonic or all studies have repeat measurements, and compare study-specific, averaged and empirical Bayes estimates of RC parameters. Additionally, we allow for binary covariates (e.g. smoking status) and for uncertainty and time trends in the measurement error corrections. Our methods are illustrated using a subset of individual participant data from prospective long-term studies ill the Fibrinogen Studies Collaboration to assess file relationship between usual levels of plasma fibrinogen and the risk of coronary heart disease, allowing for measurement error in plasma fibrinogen and several confounders. Copyright (C) 2009 John Wiley & Soils, Ltd.
KW - measurement error
KW - within-person variation
KW - meta-analysis
KW - individual participant data
KW - regression calibration
U2 - 10.1002/sim.3530
DO - 10.1002/sim.3530
M3 - Article
VL - 28
SP - 1067
EP - 1092
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 7
ER -