Course outline / EPIB-668 Introduction to Bayesian Analysis in the Health Sciences

Lawrence Joseph

Bayesian statistics

Please Note: Prof. Joseph has retired.
These pages are left up in case they prove
useful, but the pages and software will
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Courses
EPIB-668 Introduction to Bayesian Analysis in the Health Sciences
Course outline

Previous courses taught

EPIB-607 Principles of Inferential Statistics in Medicine

EPIB-613 Introduction to Statistical Software

EPIB-621 Data Analysis in the Health Sciences

EPIB-651 Bayesian Analysis in Medicine

EPIB-668 Introduction to Bayesian Analysis in the Health Sciences

EPIB-669 Intermediate Bayesian Analysis for the Health Sciences

EPIB-675 Bayesian Analysis in the Health Sciences

EPIB-682 Introduction to Bayesian Analysis in the Health Sciences

EPIB-683 Intermediate Bayesian Analysis for the Health Sciences

Publications

Methodological publications

Bayesian Sample Size

Change-point methods and applications

Diagnostic testing

Meta analysis

Other topics

Medical publications

Allergy and immunology

Bayesian software

Change-point methods and applications

Diagnostic testing

Diagnostic testing in Genetics

Links

EPIB-668 Introduction to Bayesian Analysis in the Health Sciences

Course Outline

1	Tues Sept	11	Introduction/Evaluation/Motivation/Background
			Mathematical background
2	Tues Sept	18	Basic Elements of Bayesian Analysis
3	Tues Sept	25	Bayesian Philosophy
			James Berger - Example 8 James Berger - Example 13 James Berger - Example 17 Berger and Berry - Illusion of Objectivity Dunson - Practical Advantages of Bayes in Epidemiology
4	Tues Oct	2	Simple Models I - Univariate Models
			Notes on predictive distributions R program for Normal Means - Version 1 R program for Normal Means - Version 2 R program for exact binomial confidence intervals
5	Tues Oct	9	Computation and Numerical Methods I - Introduction
6	Tues Oct	16	Computation and Numerical Methods II - Monte Carlo Integration
7	Tues Oct	23	Computation and Numerical Methods III - SIR Algorithm
			SIR program #1 SIR program #2 SIR program #3 SIR program #4 Extra Notes on SIR
8	Tues Oct	30	Computation and Numerical Methods IV - Gibbs sampler and WinBUGS
			Simple Gibbs program in R Paper on adaptive rejection sampling
9	Tues Nov	6	Computation and Numerical Methods V - More on WinBUGS
			WinBUGS Quick Reference for Model Preparation WinBUGS Quick Reference for Analysis WinBUGS program for Binomial Proportion WinBUGS program for Binomial Proportion Difference WinBUGS program for Normal Mean, Known Variance WinBUGS program for Normal Mean, Unknown Variance WinBUGS program for Linear Regression WinBUGS program for Linear Regression with Missing Data WinBUGS program for Logistic Regression WinBUGS program for Hierarchical Binomial Proportion All WinBUGS programs in one pdf file model.txt data.txt inits.txt script List of all Script commands
10	Tues Nov	13	Bayesian Linear and Logistic Regression
11	Tues Nov	20	Hierarchical Linear and Logistic Regression
			WinBUGS rats example WinBUGS seeds example WinBUGS pumps example
12	Tues Nov	27	Prior Distributions - Prior Selection and Elicitation
			Chaloner 1994
13	Tues Dec	4	Model Selection in Regression - Bayes Factors
			Bayes Factor graphical explanation Raftery 1995 BIC Example in R Kass 1995 (abstract only) WinBUGS pines example