Meta Analysis Prerequisites
Students are introduced to meta-analysis, a powerful statistical technique allowing researchers to synthesize 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.
This module is designed for MPhil and PhD students as part of the Social Science Research Methods Centre (SSRMC) training programme - a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.
- Students need a clear understanding of fundamental statistical concepts, bivariate association and linear regression
- To use the Titan Teaching Room computers you must bring your password for the Desktop Services system. Please note, your password for the Desktop Services system is distinct from your Raven/department/email password. If you are uncertain about this you are advised to go to the University Computing Service Helpdesk before the first day of class or find out more on the UCS Newcomers page.
- You must have access to the associated Moodle course page (http://www.ssrmc.group.cam.ac.uk/ssrmc-modules/before-first-session)
Number of sessions: 4
# | Date | Time | Venue | Trainer | |
---|---|---|---|---|---|
1 | Mon 6 Feb 2017 16:00 - 18:00 | 16:00 - 18:00 | Titan Teaching Room 1, New Museums Site | map | Sara Valdebenito |
2 | Mon 13 Feb 2017 16:00 - 18:00 | 16:00 - 18:00 | Titan Teaching Room 1, New Museums Site | map | Sara Valdebenito |
3 | Mon 20 Feb 2017 16:00 - 18:00 | 16:00 - 18:00 | Titan Teaching Room 1, New Museums Site | map | Sara Valdebenito |
4 | Mon 27 Feb 2017 16:00 - 18:00 | 16:00 - 18:00 | Titan Teaching Room 1, New Museums Site | map | Sara Valdebenito |
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
To enable students to draw statistical conclusions in a standardised manner from literature reviews
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
Presentations, demonstrations and practicals
- One online exercise [optional, dependent upon department]
- The SSRMC encourages all students to take the assessment
- 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
All students are expected to give feedback for each module they take...
At the end of each module, students will be sent a link to a very short evaluation form. They will also be able to find this link on the Moodle page for their course. The survey takes a few minutes to fill in, and can even be done on a mobile phone. Students that do not respond to the survey the first time, will receive regular automated reminders until the survey is completed.
Students will not be given certification or proof of attendance for any module for which they have not provided feedback.
- To gain maximum benefits from the course it is important that students do not see this course in isolation from the other MPhil courses or research training they are taking.
- Responsibility lies with each student to consider the potential for their own research using methods common in fields of the social sciences that may seem remote. Ideally this task will be facilitated by integration of the SSRMC with discipline-specific courses in their departments and through reading and discussion.
Four sessions of two hours
Once a week for four weeks
Booking / availability