A Modification of Stone's Test for Trend for Binary Outcome

Abstract

Stone (1988) suggested the “first isotonic regression estimator” as a tool for drawing inferences on possibly increased cancer case counts among several subregions around a putative source. He assumed the case counts to be Poisson distributed and therefore introduced a rare disease assumption into his approach. However, when analyzing cross sectional data one would rather refer to prevalence estimates among these subregions around a point risk source (for example the origin of chemical fallout). Therefore we applied antitonic regression estimation in Binomial distributions to derive a test statistic and a p value to test for a possible trend in the observed prevalence data around the putative source. The computation of this p value will be illustrated as well as severe difficulties concerning its interpretation. Further the Maximum Likelihood Ratio approach will be used to derive an alternative test statistic.