- Title
- Some Bayesian Methods in the Estimation of Parameters in the Measurement Error Models and Crossover Trial
- Author
- WANG, GUOJUN
- Degree
- PhD, University of Cincinnati,
Arts & Sciences : Mathematics, 2004.
- Advisor
- Dr. Siva Sivaganesan
- Pages
- 178p.
- Abstract
- 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.
- Subject Headings
- Statistics ; Mathematics
- Keywords
- MEASUREMENT ERROR MODEL; STRUCTURAL MODEL; REFERENCE PRIOR; JEFFREYS PRIOR; CROSSOVER TRIAL; FRACTIONAL BAYES FACTOR(FBF); MARKOV CHAIN MONTE CARLO SIMULATION
Document number: ucin1076852153.
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