1. BMTRY 747: Introduction Jeffrey E. Korte, PhD
BMTRY 747: Foundations of Epidemiology II
Department of Public Health Sciences
Medical University of South Carolina
Spring 2015

2. Course objectives Build understanding of epidemiologic viewpoint
Public health
Population-level questions
Individual impact/importance versus population-level impact/importance
How to count people?
Multicausal world

3. Course objectives
Build understanding of epidemiologic study design and analysis techniques
Advantages, disadvantages of study designs
Planning and execution of studies
Bias, confounding, interactions, matching
Stratification, adjustment, interpretation
Multivariable models, interpretation

4. Keys to epidemiologic research
Consideration of pitfalls before you start
Proper study design and execution minimizes bias, answers question you mean to ask
Examples: define study population
Study of racial disparities in elective C-section rate: include only women eligible for elective C-section (did not already deliver preterm); may exclude women with prior C-section; may limit to first full-term pregnancy
Study of preterm delivery: might limit to idiopathic preterm labor (exclude medical indications, fetal anomalies, etc); exclude multiple gestation (twins, triplets, etc)
Study of alcohol and lung cancer: limit to never-smokers

5. Keys to epidemiologic research
Proper analysis and interpretation
Take into account the nature of observational research: confounding, other sources of bias, questions of causality
Issues common to all research: interactions, measurement error, definition of exposures and outcomes of interest, generalizability

6. Overview of course Class time includes: Outside of class:
Go over homework
Lectures
Discussions
Work through examples
Answer student questions
Please do not do , text, surf web, etc.
Outside of class:
Homework
Project
Office hours: make appointment with TA or me

7. Homework Small occasional homeworks On homework due date:
Hand in homework by before class, or hand in extra copy at beginning of class (keep copy to take notes on if needed)
A student will present the homework at the start of class!
Student is randomly selected with replacement

8. Multi-part project Analyze a research question, using real data
Put together appropriate tables, figures, and text
Three parts: each with written report and brief presentation
Part 1: 5% of total grade for course
Part 2: 15%
Part 3: 25%

9. Multi-part project Everyone obtains their own dataset
I have some
You are encouraged to look elsewhere first, but I have to approve dataset
At least 200 study participants
Outcome should be dichotomous (final analysis will be logistic regression)
Project will involve basic analyses, testing for confounders and interaction, modeling

10. Study question
Does not have to produce novel or statistically significant result
Focus is on:
Thinking about the question and its importance
Understanding dataset you are using to answer the question
Understanding the methodology
Understanding interpretation of results

11. If results are publishable:
Let’s publish them!
I will help you

12. Project Part One Identify dataset to use (n>200)
Specify main study question/hypothesis
Main predictor, dichotomous outcome
Describe basic variables and associations
Identify 3-5 covariates of interest
5-10 minute presentation
Written report

13. Project Part Two Univariable and bivariable analyses
Test for confounding and effect modification
Lay groundwork for modeling: identify covariates and interaction terms to include
5-10 minute presentation
Written report

14. Project Part Three Multivariable modeling analyses (logistic)
Test for confounding and effect modification; compare models
Bring everything together including literature review, interpreting your results in context
10-15 minute presentation
Written report including final abstract

15. Midterm Take-home component In-class component
I will give you a dataset, and questions to answer (conduct analyses)
In-class component
Problem solving
Use of simple epi methods to make decisions, interpret results
Similar to homeworks and discussions

16. No final exam
Project Part 3 presentations will be on the last day of class.

17. Disclaimer
Many examples I will give in this course use categorical analysis techniques. This will make it easier to illustrate some of the key concepts such as bias, confounding, and interactions (effect modification).
These concepts are equally applicable to continuous variables or other types of variables (ordinal, nominal).

18. Course website http://www.musc.edu/~korte
I will post all class materials, hopefully a day ahead of time