Meta Analysis

Dr. Michael Borenstein

Aim of Course:

Meta-Analysis refers to the statistical analyses that are used to synthesize summary data from a series of studies. If the effect size (or treatment effect) is consistent across all the studies in the synthesis, then the meta-analysis yields a combined effect that is more precise than any of the separate estimates, and also allows us to conclude that the effect is robust across the kinds of studies sampled. By contrast, if the effect size (or treatment effect) varies from one study to the next, the meta-analysis may allow us to identify the reason for the variation and report (for example) that the treatment is more effective in a particular kind of patient, or in a particular dose range.

In this course we will discuss the logic of meta-analysis and the way that it is being used in many fields, including medicine, education, social science, ecology, business, and others. Participants will learn how to conduct a meta-analysis (how to compute an effect size, compute summary effects, assess heterogeneity of effects, test for differences in effect size across subgroups, and more). We will also discuss various controversies in meta-analysis (such as the question of mixing apples and oranges, the criticism of garbage-in-garbage-out). We will also draw on recent headline-making analyses such as the Avandia meta-analysis.

Participants will get hands-on experience in performing analyses using Excel(tm) and also using Comprehensive Meta-Analysis (CMA). All participants will have access to a free trial of CMA for the duration of the course. At the conclusion of the course, all participants should feel comfortable conducting a meta-analysis from start to finish using this or other software.

Who Should Take This Course:

Researchers who plan to perform a meta-analysis, or who want to be able understand meta-analyses that have been published by others.

For those enrolled in a Program of Advanced Statistical Studies, this is a required or elective course in the following Programs:

• Biostatistics (epidemiology) - elective
• Biostatistics (controlled trials) - elective
• Statistics for Social Sciences - elective

Course Program:

The course is structured as follows

The Instructor:

Dr. Michael Borenstein is co-editor (with Larry V Hedges, Dr Julian P.T Higgins, and Hannah R. Rothstein) of the book Introduction to Meta-Analysis, (Wiley, 2009) and co-editor (with Hannah Rothstein and Alex Sutton) of the book Publication Bias in Meta-Analysis: Prevention, Assessment and Adjustments. As Director of Biostat, a company that develops statistical software, Dr. Borenstein is the primary developer of Power And Precision, a computer program for sample size calculation, and of Comprehensive Meta Analysis, a computer program for meta analysis and systematic reviews. He served as Director of Biostatistics at Long Island Jewish Medical Center (1982-2002) and as Associate Professor at Albert Einstein College of Medicine (1992-2002). Dr. Borenstein has served on a number of review groups and advisory panels for the National Institutes of Health, including SBIR review groups (1994-2002) and as a member of the NIMH Data Safety Monitoring Board (1997-2001). He is an active member of the statistical advisory groups of the Cochrane and Campbell Collaborations.

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 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 Program in Advanced Statistical Studies 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:

Dec. 4, 2009 - Jan. 8, 2010
Apr. 9 - May. 7, 2010
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 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 1: Inference for a Single Variable, and Introduction to Statistics 2: Working with Bivariate Data (and, if necessary before these courses, Introduction to Statistics for Beginners or Survey of Statistics for Beginners). Familiarity with the issues of Sample Size and Power Determination (another statistics.com course) is also helpful. For additional information about course prerequisites, click here.

Course Text:

The required course text is Introduction to Meta-Analysis, by Borenstein, Hedges and Higgins (Wiley, 2009). It can be ordered directly from the publisher here. Wiley typically offers statistics.com customers up to 15% discount on this book (and all other statistics titles): enter the code aff15 in the Promotion Code field when prompted during checkout and click the Apply Discount button. (If you are located in Asia, the web procedure for your location may not accept this discount -- try calling your regional Wiley representative.). We recommend that you order this just-published text using this order form for the best chance to have it in hand prior to the course start date.

Software:

Class illustrations will be provided in the software program Comprehensive Meta Analysis (click here for details on how to get access to a special version).

Registration:

Register Online - $479
Register Online (academic) - $399 (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.

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