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We adopt a structured nonparametric prior mixture model,  which induces a monotonicity restriction for the dose\u2013response 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\u2013response relationship  as well as for other inferential objectives, as illustrated with two data sets from the literature.<\/jats:p><\/jats:sec>","DOI":"10.1111\/biom.12120","type":"journal-article","created":{"date-parts":[[2013,12,19]],"date-time":"2013-12-19T17:14:41Z","timestamp":1387473281000},"page":"95-102","source":"Crossref","is-referenced-by-count":9,"title":["A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models"],"prefix":"10.1093","volume":"70","author":[{"given":"Kassandra","family":"Fronczyk","sequence":"first","affiliation":[{"name":"Department of Statistics Rice University Houston, Texas U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Athanasios","family":"Kottas","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics and Statistics University of California Santa Cruz, California U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,12,19]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176342871"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.2307\/2528634"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1214\/12-BA709"},{"key":"e_1_2_8_5_1","unstructured":"Basu S.andMukhopadyay S.(2000).Binary response regression with normal scale mixture links. 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