Case-control isotonic regression for investigation of elevation in risk around a point source

Stone's isotonic regression method for analysing count data to estimate disease risk in relation to a point source of environmental pollution is now routinely used. This paper develops the corresponding procedure for case-control data consisting of the locations of individual cases with controls with associated covariate information. In this setting, the generalized likelihood ratio statistic to test the null hypothesis of constant risk against the alternative that risk is a monotone non-increasing function of distance from the point source is intractable. An approximate Monte Carlo test is described, extending an exact test proposed by Bithell for the situation in which there are no covariates. Interval estimates of risk as a function of distance from the point source are constructed by simulation of the sampling distribution of the isotonic regression estimator. The methodology is illustrated by two applications: one to the relative risk of larynx cancers and lung cancers near a now-disused industrial incinerator; the other to the risk of asthma in children in relation to distance of residence from the nearest main road.