• Main Page
• Downloads
• Consulting
• Curriculum Vitae
• Meta-Analysis Course

• Meta-Analysis Course
  General Info
  Course Description
  Course Format
  Course Schedule
  Prerequisites
  What to Bring
  Location
  Hotel
  Misc

On a semi-regular basis, I teach a three-day seminar on meta-analysis. On this website, you can find current information about this course.

Course Dates	TBA
Course Location	Maastricht University (see details below)
Registration Deadline	TBA

Note: This website will be updated occasionally, so please check once in a while whether new information has been posted.

Researchers trying to summarize the constantly growing body of research in the social, behavioral, and health sciences are increasingly using a technique called meta-analysis. Meta-analysis provides an entire set of statistical methods for aggregating and comparing the results from several related studies in a systematic manner. For example, in the health and behavioral sciences, meta-analysis is frequently used to determine whether a particular treatment or intervention is actually effective overall and whether the effectiveness of the treatment or intervention depends on certain study and/or subject characteristics (so-called moderator variables). The focus of this course will be on current methods and techniques of analyzing meta-analytic data.

We will start out with a short overview of the entire meta-analytic process (consisting of five steps: problem formulation, data collection, data evaluation, analysis and interpretation, and presentation of results). Next, we will examine how the results from a study can be summarized with various effect size measures. We will then delve into fixed- and random/mixed-effects models for combining effect size estimates and for examining whether the effect sizes depend on one or more moderator variables.

A major problem that may distort the results of a meta-analysis is publication bias (the fact that the published literature may not be representative of all the research that has been conducted on a particular topic). Therefore, current methods for detecting and dealing with publication bias will be discussed next. Finally, time permitting (and depending on the interests of the participants), we will examine methods for conducting sensitivity analyses, missing data issues, sequential/cumulative methods in the context of meta-analysis, meta-analytic techniques using individual subject data, methods for dealing with dependent/correlated outcomes, and Bayesian approaches to meta-analysis.

The course will consist of a mixture of lectures and hands-on tutorials to cover not only the theoretical background, but to also provide practical experience in analyzing real meta-analytic datasets with one or more software packages. The emphasis throughout the course will be more on the application of the methods than the mathematical details, but supplementary references will be provided for those interested in those details.

Note: Despite the level of detail, this schedule is tenative. The starting and ending times of the course are definite (so that you know when to arrive and when to leave), but everything in between is subject to change.

Although all aspects of the entire meta-analytic process will be discussed, emphasis will be placed on the analysis and interpretation step of a meta-analysis. Therefore, a general familiarity with meta-analysis will help to provide a better understanding of the course contents. Basic knowledge of statistical methods (e.g., regression, analysis of variance, hypothesis testing) will also be beneficial. Furthermore, course participants should have some familiarity with matrix algebra. A document providing a bit more background on the matrix algebra concepts that may be useful to know for this course can be found here. However, all efforts will be made to make the course as self-contained as possible.

To make the course run smoothly, please bring a calculator and a laptop with you. The calculator may be useful for some of the practical exercises (it does not need to be one of those fancy graphical ones). The laptop will be needed to do the computer exercises.

You should have a current version of R installed on the laptop. More information about R can be found at http://www.r-project.org/. You can download R for free at http://cran.r-project.org/ (if you use XP or Vista, choose "Windows", then "base", and then download the setup program). Although everything that you need to know to do the computer exercises will be explained in the course, it can't hurt to familiarize yourself with R a little bit ahead of time (manuals and contributed documentation can be found on the R website).

Once R is installed, you should also install the metafor package. If you have an internet connection, then you should be able to install the package by start R and typing install.packages("metafor").

Also, software to read pdf files should be installed on the laptop (e.g., Adobe Reader). In all likelihood, this is already installed anyway.

If you are unable to bring a laptop with you to the course, please let me know ahead of time (technically, not everybody needs to bring a laptop if people pair up for the exercises).

The course will be held at the Department of Methodology and Statistics, Maastricht University.

Department Location	Peter Debeyeplein 1 6229 HA Maastricht The Netherlands (for a picture of the building click here)
Arriving by Car	From the A2 (E25) traveling in the direction of Luik (Liège), take exit 55 (Randwyck). At the end of the exit, turn right into the Oeslingerbaan. At the first intersection, turn right into the Debeyelaan. Turn left at the next possibility into the Sorbonnelaan. Finally, turn right to enter the parking lot (you may have to push the bell and let the porter know that you are here for the IOPS course). For a map corresponding to these intructions, click here. From the A2 (E25) traveling in the direction of Eindhoven, take exit 56 (Groensveld). At the end of the exit, turn right into the Viaductweg. At the roundabout, go straight (the street changes its name to Rijksweg). Keep following the street for about 1km. Then turn left into the Oeslingerbaan. At the roundabout, go straight. After crossing over the bridge, turn right at the intersection into the Debeyelaan. Turn left at the next possibility into the Sorbonnelaan. Finally, turn right to enter the parking lot (you may have to push the bell and let the porter know that you are here for the IOPS course). For a map corresponding to these intructions, click here.
Arriving by Train	If you arrive by train, you should leave the train at Station Randwijck (not the main station!). Exit the station and you should be on the Universiteitsingel. Turn right into the Tanslaan. At the end of the Tanslaan turn left into the Debyelaan. After about 50m you should see the building on your right. For a map corresponding to these intructions, click here.

For hotel accomodations, you can contact the Congresbureau at Maastricht University. If you prefer to look for a hotel yourself, then Hotel Randwyck and NH Maastricht are both located just around the corner from the course location.

Instructional Language	English
Min/Max Number of Participants	10/25
Current Number of Participants	NA
Certificate for Participation	Yes