Course outline / EPIB-621 Data 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
no longer be updated. All material and
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Courses
EPIB-621 Data 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-621 Data Analysis in the Health Sciences

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 HeartData.txt
7	Mon Jan	28	Dummy variables in linear regression
			Smoking data
8	Wed Jan	30	Confounding and collinearity in linear regression
			hr.txt
9	Mon Feb	4	Interaction terms and prediction in linear regression
			fat.txt
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