Premium
Sequential monitoring of low event rates: an application in environmental epidemiology
Author(s) -
Maul Armand,
Viel JeanFrancois
Publication year - 1999
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/(sici)1099-095x(199907/08)10:4<439::aid-env366>3.0.co;2-7
Subject(s) - statistics , quantile , test statistic , econometrics , mathematics , statistic , statistical hypothesis testing , null hypothesis , monte carlo method , event (particle physics) , computer science , physics , quantum mechanics
A sequential testing procedure for monitoring epidemiological data is considered. The approach is based on a discrete time process of interim analyses using the likelihood ratio as a test statistic. Sampling continues until either some predetermined practical time limit is reached or a decision can be made about the hazard rates characterizing the populations to be compared. The stopping boundaries of the sequential testing procedure are determined so as to control type I error at a given level during the whole study. Thus, the critical threshold is derived from the exact distribution of the maximum value of the test statistic which is observed across all the monitoring times. To this end, the appropriate quantiles in the probability distributions of interest are obtained empirically by Monte Carlo simulation, assuming both the null hypothesis and given experimental conditions. The method is illustrated by an example concerning the incidence of leukaemia in young people living in the vicinity of the French La Hague nuclear reprocessing plant. On the whole the previous analyses do not provide evidence for a spatial–temporal clustering of leukaemia, at least within the space–time window which was examined around the nuclear reprocessing plant (35 km radius, time period 1978–1992). Copyright © 1999 John Wiley & Sons, Ltd.