Abstract
Grade information has been considered in Yuan et al. (2007) wherein they proposed a Quasi-CRM method to incorporate the grade toxicity information in phase I trials. A potential problem with the Quasi-CRM model is that the choice of skeleton may dramatically vary the performance of the CRM model, which results in similar consequences for the Quasi-CRM model. In this paper, we propose a new model by utilizing bayesian model selection approach - Robust Quasi-CRM model - to tackle the above-mentioned pitfall with the Quasi-CRM model. The Robust Quasi-CRM model literally inherits the BMA-CRM model proposed by Yin and Yuan (2009) to consider a parallel of skeletons for Quasi-CRM. The superior performance of Robust Quasi-CRM model was demonstrated by extensive simulation studies. We conclude that the proposed method can be freely used in real practice.
Original language | English (US) |
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Article number | e98147 |
Journal | PloS one |
Volume | 9 |
Issue number | 5 |
DOIs | |
State | Published - May 29 2014 |
ASJC Scopus subject areas
- General Biochemistry, Genetics and Molecular Biology
- General Agricultural and Biological Sciences
- General
MD Anderson CCSG core facilities
- Biostatistics Resource Group