Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jspi.2003.08.004
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dc.titleOptimal designs and limiting optimal designs for a trinomial response
dc.contributor.authorKelly Fan, S.
dc.contributor.authorChaloner, K.
dc.date.accessioned2014-10-28T05:14:06Z
dc.date.available2014-10-28T05:14:06Z
dc.date.issued2004-11-01
dc.identifier.citationKelly Fan, S., Chaloner, K. (2004-11-01). Optimal designs and limiting optimal designs for a trinomial response. Journal of Statistical Planning and Inference 126 (1) : 347-360. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jspi.2003.08.004
dc.identifier.issn03783758
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105284
dc.description.abstractDesigns for the continuation-ratio model for a trinomial response will be described. For the situation where the three response categories are: "no response", "efficacy" and "adverse reaction", both D-optimal designs and c-optimal designs for estimating the dose with the maximum probability of efficacy are found. Optimal designs are not available in closed form but designs with closed form expression are found which are approximately optimal. Motivated by these designs, a new concept is defined, "limiting optimality", where a sequence of designs is said to be optimal in an asymptotic sense for a sequence of prior distributions. A member of the sequence is approximately optimal for the corresponding prior distribution. Algebraic forms of limiting optimal designs are derived for a special case of the model where the slopes are equal. They are shown to be very efficient, provide insight, and also provide starting designs for numerical algorithms. © 2003 Elsevier B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.jspi.2003.08.004
dc.sourceScopus
dc.subjectContinuation-ratio model
dc.subjectOptimal design
dc.subjectTrinomial responses
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1016/j.jspi.2003.08.004
dc.description.sourcetitleJournal of Statistical Planning and Inference
dc.description.volume126
dc.description.issue1
dc.description.page347-360
dc.description.codenJSPID
dc.identifier.isiut000223881300020
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