title: 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-controls 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 1 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.
authors.affiliation: Centre for Biostatistics, University of Utrecht, The Netherlands.
authors.forename: I
authors.initials: I
authors.lastname: van der Tweel
authors.forename: P A
authors.initials: PA
authors.lastname: van Noord
authors.forename: R
authors.initials: R
authors.lastname: Kaaks
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D001943:Breast Neoplasms / Q000378:metabolism; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008875:Middle Aged; D009262:Nails / Q000378:metabolism; D012107:Research Design; D012189:Retrospective Studies; D012643:Selenium / Q000378:metabolism; D013223:Statistics as Topic / Q000379:methods*
chemical_list: D012643:Selenium