Meta-Analysis

This module offers an introduction to meta-analysis, a powerful statistical technique that enables researchers to synthesise evidence across multiple studies, using standardised effect sizes for a given research question. During the sessions, students will learn how to calculate treatment effects and standardised effect sizes, exploring questions such as, “What is the effectiveness of a new treatment in reducing anxiety symptoms?” or “How does physical activity correlate with cognitive decline?” Meta-analysis will also enable the testing of associations between variables across the literature, providing a comprehensive assessment of both the strength and direction of these relationships. For example, it allows researchers to examine the association between specific risk factors, such as smoking, and health outcomes like cardiovascular disease, or to evaluate how a psychological risk factor, such as chronic stress, correlates with mental health outcomes like depression. The module equips students with essential skills to draw statistically rigorous conclusions from literature reviews, making it especially valuable for those seeking to enhance the rigour and coherence of their research synthesis in the health and psychological sciences.

• Postgraduate students and staff
• Further details regarding eligibility criteria are available here

• Students need a clear understanding of fundamental statistical concepts, bivariate association and linear regression
• Students will also need to be familiar with using r-studio. If you are not familiar with using R, then we strongly recommend that you take the module Introduction to R.
• Students who are not familiar with R-studio will have the option to use Comprehensive Meta-Analysis (CMA) software; however, we are unable to provide licenses.

Session 1: Introductory session (systematic reviews and meta-analysis) and r-studio to calculate effect sizes, run meta-analysis (under fixed/random models) and produce forest plots

Session 2: Heterogeneity in effect sizes: Tau-squared, Tau and I-squared and moderator analysis.

• To understand and judge the results produced by a meta-analysis
• To learn how to compute effects sizes based on dichotomous and continuous data
• To become familiar with heterogeneity tests
• To learn how to calculate and report meta-analysis and moderator analysis.

Excel, and R

• 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

Click the "Booking" panel on the left-hand sidebar (on a phone, this will be via a link called Booking/Availability near the top of the page).

There may be an online open-book test at the end of the module; for most students, the test is not compulsory.

Moodle is the 'Virtual Learning Environment' (VLE) that CaRM uses to deliver the online materials for our courses.

CaRM instructors use Moodle to make teaching resources available before, during, and/or after classes, and to make announcements and answer questions.

For this reason, it is vital that all students enrol onto and explore their course Moodle pages once booking their CaRM modules via the UTBS, and that they do so before their module begins. Moodle pages for modules should go live around a week before the module commences, but some may be made visible to students earlier.

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