Martin Otava: Order restricted dose-response modelling

Autor: Zdeněk Hlávka <hlavka(at)>, Téma: 1. Abstrakty, Vydáno dne: 10. 09. 2014

Modelling of dose-response relationship is crucial part of multiple stages of drug development process. The type of data varies among stages, as well as approaches and methodology. Parametric methods are more suitable if experiment contains many doses (and there are enough observations per dose), non-parametric methods are applied if just few doses are investigated. Another source of variety is induced by focus of analysis. Different methods are applied for inference, for model selection and for estimation problems. Searching for threshold doses raises very interesting questions and problems, while "clinically significant result" concept is often taken into consideration.

Order restricted assumption is usual common choice for any methodology used, primary to increase the power of inference. Typically, it reduces to monotonicity assumption and inference against simple order alternatives.

In this presentation, we will review various aspects of order restricted dose-response modelling: approaches to tackle the inference, model selection, estimation, model averaging, etc. We will focus on early drug development stage, with only small dataset available. Specifically, multiple contrast tests will be introduced, together with their Bayesian alternative: Bayesian variable selection method.


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Otava, Martin and Shkedy, Ziv and Lin, Dan and Goehlmann, Hinrich W.H. and Bijnens, Luc and Talloen, Willem and Kasim, Adetayo (2014) Dose-Response Modeling Under Simple Order Restrictions Using Bayesian Variable Selection Methods. Statistics in Biopharmaceutical Research, 6(3):252-262

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