Common Statistical Errors: Over-Adjustment for Confounders and Mediators in Lifecourse Research.

Abstract

INTRODUCTION: Each year numerous studies evaluate longitudinal data within a lifecourse context with later-life health status (e.g. blood pressure) analysed with respect to repeated measures of early-life experiences (e.g. body mass index, BMI) using standard multiple linear regression. Although more sophisticated methods are available , some have been shown to be problematic, hence there remains confusion around which is the most appropriate analytical strategy. Standard multiple regression can suffer textbook errors in this lifecourse context that are sadly perpetuated. We revisit these problems to provide insight and give guidance. METHODS: We conducted a series of basic regression analyses, akin to those frequently seen in lifecourse research, on both the Avon Longitudinal Study of Parents and Children (ALSPAC) data and simulated data. The simulated data were designed to emulate the ALSPAC dataset to allow flexibility in sensitivity analyses. Additionally, we extended our simulation to a much older cohort.