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
no longer be updated. All material and
software is "as is" with no guarantees
of functionality or correctness.
Basic info FAQ
Course Outline
1 Mon Jan 7 Introduction/Motivation/Evaluation/Scope/Background
  Review of Hosmer D and Lemeshow S: Applied Logistic Regression
Review of Woodworth GG: Biostatistics: A Bayesian Introduction
Review of Gelman A, Carlin J, Stern H,and Rubin H. Bayesian Data Analysis
2 Wed Jan 9 Frequentist inferences for means and proportions
  Probability and Sampling
Inference for means
Inference for proportions
Editorial banning p-values from BASP
3 Mon Jan 14 Bayesian inferences for means and proportions
4 Wed Jan 16 Introduction to R
  R program for Bayesian normal means with known variance
5 Mon Jan 21 Simple linear regression: one variable
  R program for simple regression with CIs
Data for DMF teeth example
6 Wed Jan 23 Linear regression with two or more variables: basic concepts
  R program for multiple regression with CIs
7 Mon Jan 28 Dummy variables in linear regression
  Smoking data
8 Wed Jan 30 Confounding and collinearity in linear regression
9 Mon Feb 4 Interaction terms and prediction in linear regression
10 Wed Feb 6 Goodness of fit in linear regression
11 Mon Feb 11 Bayesian inference for linear regression models
  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 Logistic Regression
WinBUGS program for Hierarchical Binomial Proportion
12 Wed Feb 13 Model selection and predictions in linear regression
  Model Selection article by Adrian Raftery
Article comparing AIC to the BIC (and programming in SAS)
13 Mon Feb 18 Review
14 Wed Feb 20 Midterm Exam
15 Mon Feb 25 Hierarchical/random effects linear models
  CRP Data Set Formatted for R
CRP Data Set Formatted for WinBUGS
Blood Pressure Data Set with WinBUGS Program
16 Wed Feb 27 Introduction to logistic regression: Univariate
  Age and CHD Data Set in R Format
R program for logistic regression with CIs and ORs
17 Mon Mar 4 No Class -- Spring Break
18 Wed Mar 8 No Class -- Spring Break
19 Mon Mar 11 Introduction to logistic regression: Multivariate
  ICU Data Set in R Format
20 Wed Mar 13 Confounding and collinearity in logistic regression
  Low birth weight data
21 Mon Mar 18 Goodness of fit in logistic regression
22 Wed Mar 20 Bayesian analysis of logistic regression models
  Low birth weight data in WinBUGS format
23 Mon Mar 25 Model selection in logistic regression
24 Wed Mar 27 Hierarchical/random effects logistic regression
  WinBUGS program and data for osteoporosis example
Article by James Brophy illustrating multi-level hierarchical models
BUGS program by James Brophy for multi-level hierarchical models
25 Mon April 1 Missing data
  Simulated CRP Data Set
Kmetic et al: Example of how to handle non-ignorable missing data
26 Wed Apr 3 Measurement error
27 Mon Apr 8 Review
28 Wed Apr 10 Final Exam