Impact of measurement error and temporal variability on the estimation of event probabilities for risk factor intervention trials

Monte Carlo results and empirical findings from the Multiple Risk Factor Intervention Trial indicate that the degree of attenuation of logistic parameter estimates is well approximated by the reliability coefficient when the errors are assumed to be normal random variates and event probabilities are small.

Abstract

The impact of measurement error and temporal variability of risk factors on estimates of disease probabilities based on the logistic function is discussed. Monte Carlo results and empirical findings from the Multiple Risk Factor Intervention Trial indicate that the degree of attenuation of logistic parameter estimates is well approximated by the reliability coefficient when the errors are assumed to be normal random variates and event probabilities are small. In the design of intervention studies, measurement error and temporal variability of risk factors do not usually influence estimates of the probability of developing the disease in the control group, but can result in mis-estimation of the probability of developing the disease in the experimental group, substantially reducing the statistical power of the clinical trial.