Meta Analysis
In this module students will be introduced to meta-analysis, a powerful statistical technique allowing researchers to synthesize the available evidence for a given research question using standardized (comparable) effect sizes across studies. The sessions teach students how to compute treatment effects, how to compute effect sizes based on correlational studies, how to address questions such as what is the association of bullying victimization with depression? The module will be useful for students who seek to draw statistical conclusions in a standardized manner from literature reviews they are conducting.
Aims:
1. To understand and judge the results produced by a meta-analysis
2. To learn how to compute effects sizes based on dichotomous and continuous data
3. To become familiar with heterogeneity tests
4. To learn how to calculate and report subgroup analysis and meta-regression
Session 1: Computational formulas for effect sizes and their variance: fixed/random models
Session 2: Heterogeneity in effect sizes: Tau-squared, Tau, and I-squared
Session 3: Sub-group analysis and meta-regression
Session 4: Vote-counting; publication bias; criticism of meta-analysis
- Students need a clear understanding of fundamental statistical concepts, bivariate association and linear regression
Number of sessions: 3
# | Date | Time | Venue | Trainer | |
---|---|---|---|---|---|
1 | Mon 12 Feb 2018 16:00 - 18:00 | 16:00 - 18:00 | Titan Teaching Room 1, New Museums Site | map | Sara Valdebenito |
2 | Mon 19 Feb 2018 16:00 - 18:00 | 16:00 - 18:00 | Titan Teaching Room 1, New Museums Site | map | Sara Valdebenito |
4 | Mon 5 Mar 2018 14:00 - 18:00 | 14:00 - 18:00 | Titan Teaching Room 1, New Museums Site | map | Sara Valdebenito |
One online exercise
- Borenstein, M. Hedges, L.V. Higins, J.P.T. & Rothstein, H.R. (2009) Introduction to Meta-Analysis. Chichester: Wiley
- Lipsey,M.W.& Wilson,D.B. (2001). Practical Meta-Analysis. London:Sage
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