On confounding, efficiency, and prospective observational study design
Mary Margaret Ryan, PhD Candidate University of California, Irvine
Many factors must be taken into account when designing an observational study. Unlike experimental studies, observational studies cannot mitigate the effects of confounding through randomization and such factors should be incorporated into both the study analysis and the study design. Unfortunately, there is often little data available on most of these factors at the design stage, rendering it infeasible to estimate the potential confounding mechanisms. In this talk, I demonstrate how failure to account for confounding in the design stage of observational studies utilizing group sequential designs has deleterious effects on the study's observed power. I do this by constructing a hypothetical study of Alzheimer's disease biomarkers on cognition, using data from the Alzheimer's Disease Neuroimaging Initiative, then outline a procedure to use data collected at interim analyses to better estimate variance and correct stopping boundaries to maintain power.