Analysis of dose-response relationships on complex survey data

Analysis of dose-response relationships has long been important in toxicology. More recently, this type of analysis has been employed to evaluate public education campaigns. The data that are collected in such evaluations are likely to come from standard household survey designs with all the usual complexities of multiple stages, stratification and variable selection probabilities. On a recent evaluation, a system was developed with the following features: categorization of doses into three or four levels, propensity scoring of dose selection and a new jack-knifed Jonckheere-Terpstra test for a monotone dose-response relationship. This system allows rapid production of tests for monotone dose-response relationships that are corrected both for sample design and for confounding. The focus of this paper will be the results of a Monte-Carlo simulation of the properties of the jack-knifed Jonckheere-Terpstra.

Moreover, there is no experimental control over dosages and the possibility of confounding variables must be considered. Standard regressions in WESVAR and SUDAAN could be used to determine if there is a linear dose-response relationship while controlling on confounders, but such an approach obviously has low power to detect nonlinear but monotone dose-response relationships and is time-consuming to implement if there are a large number of possible outcomes of interest.