Module 9: Meta Analysis

Prerequisites

This module is part of the Social Science Research Methods Course programme which is 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.

Mphil Students from participating departments taking the Social Science Research Methods Course as part of their research degree

Students need a clear understanding of fundamental statistical concepts, bivariate association and linear regression.

• Session 1: Computational formulas for effect sizes and their variance: fixed/random models
• Session 2: Hetergeneity 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

The objective is to enable students to draw statistical conclusions in a standardised manner from literature reviews

• To learn to compute treatment effects
• To learn to compute effect sizes based on correlation studies
• To become familiar with heterogeneity tests
• To learn how to compute effect sizes based on relational studies

Presentations, demonstrations and practicals

Three exercises

• 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

• To gain the 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

Four sessions to two hours

Four times in Lent term