UCSC-SOE-12-01: A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models

Kassandra Fronczyk and Athanasios Kottas
03/21/2012 03:50 PM
Applied Mathematics & Statistics
We develop a Bayesian nonparametric mixture modeling framework for quantal bioassay settings. The approach is built upon modeling dose-dependent response distributions. We adopt a structured nonparametric prior mixture model, which induces a monotonicity restriction for the dose-response curve. Particular emphasis is placed on the key risk assessment goal of calibration for the dose level that corresponds to a specified response. The proposed methodology yields flexible inference for the dose-response relationship as well as for other inferential objectives, as illustrated with two data sets from the literature.

REVISED October 2, 2013