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Extended model‐based designs for more complex dose‐finding studies
Author(s) -
O'Quigley John,
Conaway Mark
Publication year - 2011
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4024
Subject(s) - flexibility (engineering) , computer science , bayesian probability , mathematical optimization , econometrics , artificial intelligence , mathematics , statistics
We discuss extensions of model‐based designs, such as the continual reassessment method, for use in dose‐finding studies. Rather than work with a single model to carry out the design and analysis of a dose‐finding study we indicate how the use of several models can greatly increase flexibility. We can appeal to established results on Bayesian model choice and this device makes the inferential problem essentially straightforward. The greater flexibility enables us to take on board many different kinds of added complexity. Examples include extended models to deal with subject heterogeneity, extended models to take account of different treatment schedules and extended models to tackle the problem of partial ordering. Copyright © 2011 John Wiley & Sons, Ltd.