title: Use of computer simulation to evaluate a putative cluster of genetic or teratologic outcomes: adjustment for "multiple hypotheses" and application to a reported excess of Down's syndrome.
abstract: The identification of an apparent excess of a genetic outcome in a particular area and/or a particular time often provokes considerable public alarm about the presence of an environmental mutagen. It is often difficult to determine in any particular case whether the observation, whatever its nominal statistical significance, is due to chance concatenation of events or to an environmental factor. Statistical evaluation is made more difficult by the profuse number of possible hypotheses that could have triggered concern about an excess. This renders it difficult to calculate the actual probability of the observation (or one more extreme). By attempting to identify similar types of outcomes that could have provoked an apparent excess and then undertaking computer simulations assuming random deviations from a constant rate, one may attempt to adjust for the problem of multiple hypotheses. We apply this approach to a reported excess of Down's syndrome in Norway in 1985-1986 in younger mothers, and conclude that there is a high probability that it arose by chance.
authors.affiliation: School of Public Health, University of California, Berkeley 94720-7360, USA.
authors.forename: E B
authors.initials: EB
authors.lastname: Hook
authors.forename: A D
authors.initials: AD
authors.lastname: Carothers
mesh_terms: D000293:Adolescent; D000328:Adult; D016000:Cluster Analysis; D003198:Computer Simulation; D004314:Down Syndrome / Q000453:epidemiology / Q000235:genetics*; D005260:Female; D006801:Humans; D008423:Maternal Age; D008875:Middle Aged; D008957:Models, Genetic; D009664:Norway / Q000453:epidemiology; D011159:Population Surveillance; D011247:Pregnancy; D011256:Pregnancy Outcome / Q000453:epidemiology / Q000235:genetics*; D018566:Pregnancy, High-Risk; D012189:Retrospective Studies; D018600:Teratology / Q000706:statistics & numerical data*