Abstract:
: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.
journal_name
Biometricsjournal_title
Biometricsauthors
Fronczyk K,Kottas Adoi
10.1111/biom.12120subject
Has Abstractpub_date
2014-03-01 00:00:00pages
95-102issue
1eissn
0006-341Xissn
1541-0420journal_volume
70pub_type
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