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