title: Inference for the existence of hormetic dose-response relationships in toxicology studies.
abstract: In toxicology studies hormesis refers to a dose-response relationship with a stimulatory response at low doses and an inhibitory response at high doses. In this manuscript, we particularly focus on a J-shaped dose-response relationship for binary cancer responses. We propose and examine two new flexible models for testing the hypothesis of hormesis in a Bayesian framework. The first model is parametric and enhances the flexibility of modeling a hormetic zone by using a non-linear predictor in a multistage model. The second model is non-parametric and allows multiple model specifications, weighting the contribution of each model via Bayesian model averaging (BMA). Simulation studies show that the non-parametric modeling approach with BMA provides robust sensitivity and specificity for detecting hormesis relative to the parametric approach, regardless of the shape of a hormetic zone.
authors.affiliation: Department of Mathematics and Statistics, California State University, Monterey Bay, Seaside, CA 93955, USA stkim@csumb.edu.
authors.forename: Steven B
authors.initials: SB
authors.lastname: Kim
authors.affiliation: Department of Statistics, University of California, Irvine, Irvine, CA 92697, USA.
authors.forename: Scott M
authors.initials: SM
authors.lastname: Bartell
authors.affiliation: Department of Statistics, University of California, Irvine, Irvine, CA 92697, USA.
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Gillen
mesh_terms: D001499:Bayes Theorem; D059165:Hormesis; D006801:Humans; D008962:Models, Theoretical; D014116:Toxicology / Q000379:methods*
keywords: Bayesian model averaging; Hormesis; Hypothesis testing; Multistage models; Non-parametric models