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
"Michael clearly explained some of the basic concepts of meta-analysis (e.g. Random vs. fixed effects models; interpreting heterogeneity scores; subgroup analysis) in a way that made these sometimes-confusing issues clear. He also exposed some of the myths and mistakes that are common in many published Meta-Analysis."
Christina Pallitto - WHO
"It was a very informative seminar. I feel much more confident in doing meta-analysis now. Thank you."
Karine Dubois-Comtois - University of Quebec at Trois-Rivieres