Correcting for multivariate measurement error by regression calibration in meta‐analyses of epidemiological studies
Population
Subset of individual participant data from prospective long-term studies in the Fibrinogen Studies…
Comparison
Multivariate regression calibration techniques… vs Study-specific, averaged, and empirical Bayes…
Design
Other
Authors
Discussion
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Implication
Enables more accurate meta-analytic risk estimates; extends multivariate calibration to binary covariates with uncertainty and trends.
Structured PICO
P
Population
Subset of individual participant data from prospective long-term studies in the Fibrinogen Studies Collaboration
I
Intervention
Multivariate regression calibration (RC) techniques extended to a meta-analysis framework
C
Comparator
Study-specific, averaged, and empirical Bayes estimates of RC parameters
O
Outcome
Relationship between usual levels of plasma fibrinogen and the risk of coronary heart disease
The study provides an extended multivariate regression calibration method for meta-analyses to correct for measurement error in multiple risk factors, illustrated by assessing plasma fibrinogen and coronary heart disease risk.
Cite This Study
Daan Kromhout (2009) studied this question.