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SOME BAYESIAN METHODS IN THE ESTIMATION OF PARAMETERS IN THE MEASUREMENT ERROR MODELS AND CROSSOVER TRIAL

by WANG, GUOJUN

Abstract (Summary)
In this dissertation, we use Bayesian methods to estimate parameters in measurement error models and in the two-period crossover trial. The reference prior approach is used to estimate parameters in the measurement error models, including simple normal structural models, Berkson models, structural models with replicates, and the hybrid models. Reference priors are derived. Jeffreys prior is obtained as a special case of reference priors. The posterior properties are studied. Simulation-based comparisons are made between the reference prior approach and the maximum likelihood method. A fractional Bayes factor (FBF) approach is used to estimate the treatment effect in the two-period crossover trial. The reference priors and the FBF are derived. The FBF is used to combine the carryover-effect model and the no-carryover-effect model. Markov chain Monte Carlo simulation is used to implement the Bayesian analysis.
Bibliographical Information:

Advisor:

School:University of Cincinnati

School Location:USA - Ohio

Source Type:Master's Thesis

Keywords:measurement error model structural reference prior jeffreys crossover trial fractional bayes factor fbf markov chain monte carlo simulation

ISBN:

Date of Publication:01/01/2004

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