My MSc thesis is focused on parametric designs of Phase I clinical trials, using the continual reassessment method. A parametric model with unknown parameters is assumed. The observations are either toxic or nontoxic. Observations of toxicities are used to update the posterior distribution. Dose selection for the next patient is based on the estimated toxicity probability. The objective is to identify the maximum tolerated dose to be used in Phase II clinical trials. We introduce a new class of parametric functions for the continual reassessment method. This class is formed with the cumulative distribution function of the normal distribution. The major advantage is that we can choose different normal distributions to model different toxicity probability functions. We conduct simulation studies and compare our new design with the existing parametric designs, and have found that our design performs better by choosing the appropriate values of the mean and variance. / October 2016
| Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/31795 |
| Date | 16 September 2016 |
| Creators | Zhang, Weijia |
| Contributors | Yang, Po (Statistics), Mandal, Saumen (Statistics) Cai, Jun (Electrical Computer Engineering) |
| Source Sets | University of Manitoba Canada |
| Detected Language | English |
Page generated in 0.0019 seconds