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
"I would definitely recommend taking this course. It has direct application for anyone who is interested in performing meta-analysis. I was very surprised that we even looked at meta-regression, which expands the ability to analyze data."
Dr. Maxine Strickland, DmD, MPH - Rutgers School of Medicine
"A detailed course with a wealth of resources provided. I have learnt a lot but now need to put it into practice."
Dr. E. Derbyshire, Senior Lecturer - Manchester Metropolitan University