BHI EE Programme: Meta Analysis

COURSE AIM AND CONTENT

This course is designed to introduce students to the statistical techniques used in meta-analysis, the synthesis of data from different studies. It will enable participants to utilize these techniques in their own meta-analyses and facilitate the interpretation and critique of existing meta-analyses. Practical examples will be drawn from the mental health field. Upon completion of this course it is intended that students will be able to:

• Calculate the statistical tests to run a meta-analysis under different settings and assumptions
• Know how to run a variety of common meta-analyses; for single-group means, two-sample mean differences (independent and dependent), two-group binary outcomes and correlation coefficients
• Understand and be able to explain the difference between fixed-effects and random-effects meta-analyses and choose which is appropriate in relevant context
• Assess heterogeneity across studies
• Understand and calculate the following statistics data: Cohen’s d, Hedges g, risk ratio, odds ratio, risk difference, Fisher’s z, T-squared, Q, I-squared
• Use a funnel plot to assess publication bias
• Perform a meta-analysis when outcome metrics differ across studies

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