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• Meta-Analysis Course

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

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

Course Dates	November 21-23, 2011
Course Location	Maastricht University (see details below)
Registration Deadline	November 11, 2011

This course is sponsored by the Interuniversity Graduate School of Psychometrics and Sociometrics (IOPS). Information on the course fees and registration can be found below.

Note: This website is updated occasionally, so please check back once in a while to see if 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 encompasses 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 for 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. The use of so-called meta-regression models will be emphasized in this context.

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 consists 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 is focused 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 tentative. The starting and ending times of the course are definite, 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 (R is a software environment for statistical computing and graphics). 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, Vista, or Windows 7, choose "Windows", then "base", and then download the setup program; versions for Linux and MacOS X are also available). 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, please install the metafor package (an add-on for conducting meta-analyses with R). More details about the package can be found at http://www.metafor-project.org/. If you have an internet connection, you should be able to install the package by starting R and then 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 fee includes lunch on all three days, refreshments (e.g., coffee, tea, water) during the breaks, but not dinner or accommodations.

To register for the course, please complete the registration form (pdf or doc) and send it by regular mail, fax, or e-mail to:

Wendy Beuken
Department of Psychiatry and Neuropsychology
Maastricht University
P.O. Box 616 (VIJV)
6200 MD Maastricht
The Netherlands

Fax: +31 (43) 368-8689
E-mail: w.beuken (at) maastrichtuniversity.nl

The course will be held at the Department of Psychiatry and Neuropsychology at Maastricht University in the Netherlands.

Department Location	Vijverdalseweg 1 6226 NB Maastricht The Netherlands Google Maps Link
Arriving by Car	From the A2/E25 traveling in the direction of Luik/Liège, take a left at the first stoplight, turning into the Terblijterweg/Viaductweg. Follow the road, passing one roundabout, for about 1.6km. Turn right into the Vijverdalsweg. At the roundabout, take the third exit (i.e., turn left) into Bergerstraat. Take a right into the parking lot (if the gate is closed, please ring the bell).
	From the A2/E25 traveling in the direction of Eindhoven, take a right into the Scharnerweg. Follow the road, passing one roundabout, for about 600m. Take a slight left into the Bergerstraat (you are really just following the main road). At the roundabout, take the second exit (i.e., go straight). Take a right into the parking lot (if the gate is closed, please ring the bell).
	For a map corresponding to these intructions, click here.
Arriving by Train	If you arrive by train, you should leave the train at the main station in Maastricht. Exit the station and take bus number 10 in the direction "AZM (Academisch Ziekenhuis) via Heer" (the bus leaves twice every hour, at 24 and at 54 minutes past the hour). Take the bus to the Vijverdal stop (takes about 10 minutes). The building is right across the road from the bus stop.

For hotel accomodations, you can contact the Congresbureau at Maastricht University. If you prefer to look for a hotel yourself, then some possible options include the Novotel Hotel, Hotel van der Valk, and Hotel in den Hoof. All three hotels are located around 1.7km from the course location (note that Hotel in den Hoof is really on the outskirts of the city). For a map showing the course location and the location of these hotels, click here.

Instructional Language	English
Min/Max Number of Participants	10/20
Certificate for Participation	Yes
Number of European Credit Points	1