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Analysis of Epidemiologic Data

Dr. David G. Kleinbaum
Prof. Nancy Barker

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 Fundamentals of Epidemiology and Bias in Epidemiologic Research.

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.

For those enrolled in Professional Advancement Programs, this is a required or elective course in the following Programs:

  • Biostatistics (epidemiology) - required

Course Program:

The course is structured as follows

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

The Instructor:

The instructors are Professor David G. Kleinbaum at Emory University's Rollins School of Public Health and Nancy Barker, consulting biostatistician/epidemiologist and Instructor in Emory University's Career MPH Program.

Professor Kleinbaum is internationally known for his textbooks in statistical and epidemiologic methods and as an outstanding teacher. He is the author of Epidemiologic Research- Principles and Quantitative Methods (Wiley, 1982), Applied Regression Analysis and Other Multivariable Methods, 3rd Edition (Duxbury, 1997), Logistic Regression- A Self-Learning Text, 2nd edition (Springer, 2002), and Survival Analysis- A Self Learning Text, 2nd edition (Springer, 2005). His recent "electronic" textbook ActivEpi and its accompanying ActivEpi Companion Text (Springer, 2003) serve as the texts for this course. He has also taught over 150 short courses over the past 30 years throughout the world.

Nancy Barker is a consulting biostatistician and a co-author of the ActivEpi Companion Text, and has over 10 years of experience teaching short courses in epidemiology and biostatistics at Emory University and the Centers for Disease Control and Prevention.

Organization of the Course:

The course takes place over the internet, at statistics.com. 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 is scheduled to take place over 4 weeks, and typically requires 10-15 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 and work through exercises. Discussion among participants is encouraged. The instructor will provide answers and comments.

Certificates and Grades:

You may be interested only in learning the material presented, and not be concerned with grades or certificates. Or you may be enrolled in a statistics.com Professional Advancement Program that requires demonstration of proficiency in the subject, in which case your work will be assessed for purposes of issuing a grade. Or you may require only a "Certificate 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.

Credit:

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 certificate will be issued by statistics.com, upon request.

Dates:

Oct. 10 - Nov. 7, 2008
Click here to be notified of future course offerings.

Participants gain access to the online materials on the first day of the course, and typically spend about 10-15 hours per week (at their convenience). You retain full access to course materials, including discussion board, for two weeks after the course closing date.

Level:

Intermediate

Prerequisite:

The equivalent of Introduction to Statistics I: Inference for a Single Variable, and Introduction to Statistics II: Working with Bivariate Data (and, if necessary before these courses, Introduction to Statistics for Beginners or Survey of Statistics for Beginners). 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 Text:

The required text is ActivEpi, Version 1.1 and its accompanying ActivEpi Companion Text, Springer Publishers, 2003. The previous links allow you to purchase these items directly from Springer. Springer typically 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!

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.

Registration:

Register Online - $449
Register Online (academic) - $349 (you must be affiliated with a college, university or high school)

Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Note: Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.