THE METAFOR PACKAGE

R LogoIf you are looking for information about the metafor package for R, please go to the Downloads section.

NEWS/UPDATES

July 22, 2010: I am still not sure when I will give the meta-analysis course again. Due to various reasons, I have to hold off on making plans for the Fall.

March 18, 2010: If you are wondering if I am giving my meta-analysis course this year, please be patient. I am in the process of deciding when (and in what form) I will give the course again. More information about the course will be posted here eventually.
Wolfgang Viechtbauer
Department of Methodology and Statistics
School for Public Health and Primary Care
Maastricht University
P.O. Box 616
6200 MD Maastricht
The Netherlands

Contact:
Tel: +31 (43) 388-2277
Fax: +31 (43) 361-8388
E-Mail: wvb (at) wvbauer (dot) com

Office/Visiting Address:
Room B2.01 (second floor)
Peter Debyeplein 1 (Randwyck)
6229 HA Maastricht

Short Profile ...

I am currently working as an assistant professor in the Department of Methodology and Statistics at Maastricht University in the Netherlands. The Department of Methodology and Statistics is part of the Faculty of Health, Medicine and Life Sciences (FHML). My position falls under the School for Public Health and Primary Care. I was born in Aachen, Germany, moved to the United States when I was 16, and then spent the next 11 years of my life in the United States. After receiving my Ph.D. in 2004 from the University of Illinois, Urbana-Champaign, I moved back to Europe and started working at Maastricht University. My research is primarily focused on the statistical methods used for meta-analyses, but I am interested more generally in mixed-effects models as used for the analysis of longitudinal and multilevel/hierarchical data. I currently teach a course on research methods at the University College Maastricht (UCM) and co-teach several courses on various statistical methods for students in the Health Sciences and Public Health programs.

Current Research Interests ...
  • meta-analysis
  • mixed-effects models
  • longitudinal data analysis
  • multilevel models
  • effect size measures