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Introduction To Meta-Analysis (Online, self paced)

  • 6 hours
  • 1 day

Overview

This course provides an overview of meta-analysis from a statistician's point of view and is delivered by UCL's Centre for Applied Statistics Courses (CASC), part of the UCL Great Ormond Street Institute of Child Health (ICH).

Content

You'll be introduced to the merits of meta-analysis and how it can form an important and informative part of a systematic review.

Tutors explain the most common statistical methods for conducting a meta-analysis and common issues that may be encountered along the way. The following topics are covered:

  • An introduction to meta-analysis and its place in evidence-based research.
  • Outcome measures and extracting relevant data from journal articles
  • Fixed effect and random-effects models
  • Heterogeneity between studies
  • How to identify and deal with publication bias.

Related topics that we don't cover on this course are (1) how to conduct a systematic search of the literature, and (2) assessing the quality of studies in a meta-analysis.

Course structure and teaching

This is an online, self-paced course which includes: 

  • full electronic notes 
  • short lecture videos (recorded outside of the classroom) that follow closely with the notes 
  • interactive quizzes for each chapter 
  • extended practical exercises (with solutions) for further comprehension 

The course is likely to take about six hours to complete, but can be studied at your own pace. 

Support will also be available through a forum, where you can ask questions related to the course materials.

Learning outcomes

At the end of the course, delegates should be able to conduct a meta-analysis of their own and interpret the results of meta-analyses published in journal articles. In particular, delegates will be able to:

  • Understand what meta-analysis is and when it’s appropriate.
  • Extract the relevant data from quantitative journal articles.
  • Perform simple calculations to get the data in the correct format ready for meta-analysis
  • Understand the underlying theory behind the most common statistical models, and what they assume.
  • Quantify and explore heterogeneity between studies through meta-regression and subgroup analysis.

Entry requirements

A basic level of statistical literacy is required as a prerequisite.

In particular, you should have a basic understanding of standard errors, p-values and confidence intervals.

Those who have completed the five-day Introduction to Statistics and Research Methods course run frequently by the Centre for Applied Statistics Courses (CASC) team will be equipped.

Cost and concessions

The standard price is £75.

A 50% discount is available for UCL staff, students and alumni. If you're eligible for a discount, email ich.statscou@ucl.ac.uk before booking to be sent the discount code.

The course is available for free to those associated with the Institute of Child Health or Great Ormond Street Hospital, and SLMS doctoral students. Please also email ich.statscou@ucl.ac.uk to gain a booking code. 

Certificates

You can download a certificate of participation once you have completed all the session quizzes.

Find out about other statistics courses

CASC's stats courses are suitable for anyone requiring an understanding of research methodology and statistical analyses. The courses allow non-statisticians to interpret published research and/or undertake their own research studies.

Find out more about CASC's full range of statistics courses.
 

Course team

Dr Dean Langan

Dr Dean Langan

Dean works as a lecturer, jointly based within the School of Life and Medical Sciences (SLMS) and the Centre for Applied Statistics Courses (CASC) at UCL. He has a Bachelor’s degree in Mathematics from University of Liverpool, a Master's degree in Medical Statistics from University of Leicester, and a PhD from University of York for his research in statistical methods for random-effects meta-analysis. He's worked as a statistician on a number of clinical trials related to stroke and myeloma at the Clinical Trials Research Unit in Leeds. His specialist areas include statistical methods for meta-analysis, R programming, clinical trial methodology and research design.

Course information last modified: 23 Oct 2023, 15:58