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Abstract:
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Bayesian statistical approach is a famous methodology in clinical trial studies. Toxicologist aim for a better dose-response model that fit the data well and determine the tolerable region under that fit. Multivariate monotonic decreasing spline fitted to toxicology data, to detriment the tolerable region of multiple chemicals. Knowing what is the best and the acceptable level of this chemical has been investigated using a different methodology approach. Our novel approach is an expansion to K-dimension of Alamri monotonic spline which was developed for one dimension. In this project, we generate a bivariate nonparametric regression spline that fits the properties of the dose-response model using Markov Chain Monte Carlo sampling. However, there is still a preferable tolerable region under less interaction between the endpoint, which is the goal of this research. Examples of simulated data and real-life data will be used to demonstrate the use and effectiveness of this method.
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