Asymptotically Informative Prior for Bayesian Analysis

A Bayesian design and analysis for dose-response using informative prior information.

We wish to use prior information on an existing drug in the design and analysis of a dose-response study for a new drug candidate within the same pharmacological class. Using the Bayesian methodology, this prior information can be used quantitatively and the randomization can be weighted in favor of the new compound, where there is less information. An Emax model is used to describe the dose-re...

Normalized Power Prior Bayesian Analysis Normalized Power Prior Bayesian Analysis

Weakly Informative Prior for Covariance Matrices 1 Running head: WEAKLY INFORMATIVE PRIOR FOR COVARIANCE MATRICES Weakly Informative Prior for Point Estimation of Covariance Matrices in Hierarchical Models

When fitting hierarchical regression models, maximum likelihood estimation has computational (and, for some users, philosophical) advantages compared with full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix (Σ) of group-level varying coefficients are often degenerate. One can do better, even from a purely point-estimation perspective, by using a p...

A Bayesian Modelling Approach with Balancing Informative Prior for Analysing Imbalanced Data.

When a dataset is imbalanced, the prediction of the scarcely-sampled subpopulation can be over-influenced by the population contributing to the majority of the data. The aim of this study was to develop a Bayesian modelling approach with balancing informative prior so that the influence of imbalance to the overall prediction could be minimised. The new approach was developed in order to weigh t...

Physiological pharmacokinetic analysis using populationmodeling and informative prior distributions

We describe a general approach using Bayesian analysis for the estimation of parameters in physiological pharmacokinetic models. The chief statistical diiculty in estimation with these models is that any physiological model that is even approximately realistic will have a large number of parameters, often comparable to the number of observations in a typical pharmacokinetic experiment (for exam...