Agenda » Learning objectives
Course learning objectives
Basic course
The objective of this course is to introduce students to the logic of a basic meta-analysis and teach them how to perform a meta-analysis, critique a meta-analysis, and avoid common mistakes in meta-analysis. By the end of the course students will understand
- The goals of a meta-analysis
- How to choose a statistical model
- How to choose an effect-size index
- How to enter data for a simple meta-analysis
- How to estimate the mean effect size
- How to quantify and understand heterogeneity in effects
- How to report the results of the analysis
- How to create forest plots
- How to create plots that show the distribution of true effects
- How to avoid common mistakes in all these areas
Advanced course
The objective of this course is to teach students advanced issues in meta-analysis. By the end of the course the student will understand
- How to use subgroup analyses to compare the impact of a treatment in sets of studies that enrolled different populations or employed different variants of an intervention (analogous to ANOVA in a primary study)
- How to use meta-regression to assess the unique impact of continuous or categorical covariates on the effect size (analogous to multiple-regression in a primary study)
- How to assess the potential impact of publication bias on the analysis
- What to do when there are only a small number of studies in the analysis
- How to avoid common mistakes in all these areas
Testimonials
"The discussion of theory and practice throughout the course allows you to start to use this technique the next day."
Marco A. Magalhaes - WHO
"No matter if you’re a clinician, researcher or statistician; the course offers you a broad theoretical as well as practical intro to the discipline of meta-analysis. Everyone seemed to learn something – this shows great competence of Michael Borenstein."
Christina Mohr Jensen - Research Unit for Child & Adolescent Psychiatry