Shrinkage priors for isotonic probability vectors and binary data modeling, with applications to dose–response modeling
Philip S. Boonstra,
Daniel R. Owen,
Jian Kang
Abstract:Motivated by the need to model dose–response or dose‐toxicity curves in clinical trials, we develop a new horseshoe‐based prior for Bayesian isotonic regression modeling a binary outcome against an ordered categorical predictor, where the probability of the outcome is assumed to be monotonically non‐decreasing with the predictor. The set of differences between outcome probabilities in consecutive categories of the predictor is equipped with a multivariate prior having support over simplex. The Dirichlet distri… Show more
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