Epi 3: Analysis of Epidemiologic Data

Brief Description:

This is a second level epidemiology course that emphasizes methods for analyzing epidemiologic data. Topics covered in the course include: simple analysis of 2x2 tables, control of extraneous variables (including an introduction to logistic regression), stratified analysis, and matching.

Instructor(s):
Level: Intermediate

Who Should Take This Course:

Administrators, practicing professionals, researchers, graduate or undergraduate and even high school students in the health, medical, and behavioral sciences interested in learning fundamental principles and methods of epidemiologic and public health research. This course is also intended to address increasing demands to provide training to public health professionals and students in developing countries that do not have convenient access to academic training in epidemiology and related public health fields.

Dates:
All courses have already commenced.
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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

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Epi 3: Analysis of Epidemiologic Data

Aim of Course:

This is a second level epidemiology course that emphasizes methods for analyzing epidemiologic data. Topics covered in the course include: simple analysis of 2x2 tables, control of extraneous variables (including an introduction to logistic regression), stratified analysis, and matching. See also the companion courses Epi 1: Fundamentals of Epidemiology and Epi 2: Designing Epidemiologic Studies.

This course is a core requirement or elective in the following Program(s) in Advanced Statistical Studies (PASS):

• Biostatistics (Epidemiology)

Prerequisite(s):

Course participants should also have some previous knowledge and experience with fundamental concepts in epidemiologic research, in particular, epidemiologic study designs, measures of frequency and effect, confounding, and interaction/effect modification. The mathematics level is basic algebra.

Course Program:

SESSION 1: Simple analysis of 2x2 tables

• Overview of simple analysis
• Review of statistical inference procedures: hypothesis testing and confidence interval estimation
• Cohort studies involving rate ratios
• Case-control studies
• Cohort studies involving rate ratios

SESSION 2: Control of extraneous variables

• Definition and reasons for control
• Overview of options for control
• Randomization
• Restriction
• Matching
• Stratified Analysis
• Mathematical modeling: linear and logistic regression

SESSION 3: Stratified analysis

• Examples involving one and several control variables
• When to do or not do overall assessment
• Testing for overall association: Mantel-Haenszel test
• Overall assessment using adjusted estimates: precision-based and Mantel-Haenszel methods
• Interval estimation of adjusted estimates
• Extensions to more than two exposure categories
• Testing for overall association using logistic regression

SESSION 4: Matching

• Definition and examples of matching
• Types of matching
• Matching ratiios
• How many matches should you select
• Reasons for and against matching: to match or not to match
• Analysis of matched data: options and principles
• Analysis of pair-matched case-control data
• Analysis of R-to-1 matched case-control data
• Pooling matched data
• Analysis of frequency-matched data
• Analysis of matched cohort data
• Logistic regression: matched and unmatched covariates

Organization of the Course:

This course takes place over the internet, at statistics.com for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

The course typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and you will receive individual feedback on your homework answers.

Credit:
Students come to The Institute for a variety of reasons:

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Program in Advanced Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).

As you begin the class, you will be asked to specify your category.

This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a record of course completion will be issued by Statistics.com, upon request.

Course Text:

The required course material is ActivEpi, Version 2 courseware(on CD) and its accompanying ActivEpi Companion Text, Springer Publishers, 2003. This companion text in electronic form is contained on the ActivEpi CD. If you wish, you may purchase a printed version of the companion text here. The previous links allow you to purchase these items directly from Springer. Springer offers a 15% discount when you use the order code AECT15 during check out. PLEASE ORDER YOUR COPY IN TIME FOR THE COURSE STARTING DATE! Currently the expected publication date for the ActivEpi CD is Sept. 24, so please preorder.

Software:

Software capable of doing survival analysis will be needed. Any package can be used; instructions and support will be provided for a free package called OpenEpi. For information on obtaining OpenEpi and other software for use during this course, please click here.

R: If you want to use R with this course, you should have some prior experience and facility with it. Help from the TA will be available but limited. If you wish to use R, but no have current expertise in it, you should consider taking one of our introductory R courses before taking this one.

SAS: If you want to use SAS with this course, you should have some prior experience and facility with it. If you wish to use SAS, but no have current expertise in it, you should consider taking our SAS - Basics course before taking this one.

Stata: If you want to use Stata with this course, you should have some prior experience and facility with it. Help from the TA will be available, but limited.

For more information on the above mentioned statistical software, please click here.

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Epi 3: Analysis of Epidemiologic Data

Instructor(s):
Dates:
All courses have already commenced.
Course Fee: $499
Academic Discounted Rate: $399

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