Application of a sequential t-test in a cohort nested case-control study with multiple controls per case

Abstract

Application of sequential analysis may avoid unnecessary experimentation and achieve economical use of available biomaterial stored in biological banks. When, as often happens in cohort case-control studies, cases are scarce, it may be possible to use multiple control observations per case to increase the power of a test for detecting differences between cases and controls. Samples from a biological data bank were analysed. We compared results of a non-sequential analysis with results of sequential t-tests for I to 5 controls matched per case in a cohort nested case-control study. Simulations are performed to get an idea of the unreliability and the power of the sequential test. In general the sequential t-tests are too conservative with respect to the achieved power. Average sample numbers are lower for the sequential tests and decrease with multiple controls. More than 3 or 4 controls per case does not give a meaningful increase in efficiency.