Computer modelling of measurement error in longitudinal lung function data

Abstract

The effect of measurement error on the accuracy of results in two epidemiological study designs involving longitudinal lung function data was assessed using computer modelling. Five realistic data sets (cohorts) were created, each of 400 subjects, half of whom were exposed to an agent whose effects approximated in magnitude that of cigarette smoking. In each cohort, FEV₁ decline was modelled after 6, 4 and 2 years of observation with and without error in the measurement of level of FEV₁. For each length of observation the effect of exposure on decline was estimated using a follow-up design comparing the FEV₁ decline between exposure groups, and a case-control design comparing risk of exposure in subjects in the top 20th percentile of FEV₁ decline (cases) to exposure in those in the bottom 20th percentile (controls). For both study designs an exposure effect at $\text{p}\textcolor{red}{}\text{0.01}$ could only be consistently detected after 6 years of observation.