The effect of non-random loss to follow-up on group mean estimates in a longitudinal study.

Abstract

Bias due to selective non-response is often neglected in large-scale epidemiological studies. And, although some recent techniques enable adjustment for selective non-response, these are rarely applied. The Maastricht Cohort Study, a study on fatigue at work among 12140 respondents at baseline, enabled us to estimate the degree of bias in a real life data set. After seven subsequent measurements, spanning a 2-year period, 8070 respondents remained in the cohort. Two traditional ways of presenting longitudinal mean levels (means using all data, and means using only complete cases) are compared with adjusted mean levels, using mixed models. The difference between the complete case and overall mean levels and the adjusted means were about 2% for the continuous fatigue score and 6% for the proportion of fatigued cases. For the company mean scores the observed bias due to selective non-response might be as much as 30% for some of the company means for the continuous fatigue score and up to 160% for the estimated number of fatigued cases. We therefore conclude that bias due to selective non-response needs serious attention. Next to making vigorous attempts to minimize longitudinal non-response, the use of statistical adjustment is also recommended.