IJE Advance Access originally published online on July 28, 2005
International Journal of Epidemiology 2005 34(6):1359-1368; doi:10.1093/ije/dyi148
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Theory and Methods |
The effect of measurement error in risk factors that change over time in cohort studies: do simple methods overcorrect for ‘regression dilution’?
1 Department of Epidemiology and Population Health, Medical Statistics Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
2 MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge, UK.
* Corresponding author. Department of Epidemiology and Population Health, Medical Statistics Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK. E-mail: chris.frost{at}lshtm.ac.uk
Background The attenuation of the relationship between disease and a risk factor subject to error through ‘regression dilution’ is well recognized, and researchers often make attempts to adjust for its effects. However, the adjustment methods most often adopted in cohort studies make an implicit assumption that the relationship is driven exclusively by current error-free levels of the risk factor and not by past levels. Here we investigate the bias that is introduced if this assumption is invalid.
Methods We model disease risk at a particular time in terms of error-free levels of the risk factor at that time and in past periods, and summarize the ‘life-course’ risk factor-disease relationship using crude current level, history adjusted current level and lifetime level associations. Using systolic blood pressure data from the Framingham Heart Study we show the impact of measurement error on these associations and investigate the biases that can occur with simple correction methods.
Results A simple ‘ratio of ranges’ type correction factor overestimates the lifetime level association by 29% in the presence of a relatively modest dependency of current risk on past levels (levels 5 years ago half as predictive of current risk as current levels).
Conclusions Simple methods of correction for regression dilution bias can lead to substantial overcorrection if the risk factor-disease relationship is not short term.
Keywords Regression dilution bias, measurement error, cohort studies, ratio of ranges, Framingham study, blood pressure
Accepted 21 June 2005
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