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Meta-analysis: an Introduction

  • 5 hours (one day), or 8 hours (two days)
  • 1 or 2 days (day 2 optional)
  • 27 March 2019

Overview

This short course provides an overview of meta-analysis from a statistician’s point of view.

You'll learn about:

  • the merits of meta-analysis and how it can form an important and informative part of a systematic review
  • the most common statistical methods for conducting a meta-analysis
  • common issues that may be encountered 

By the end of the course you should be able to conduct a meta-analysis of your own and interpret the results of meta-analyses published in journal articles.

It runs over one full day, with an optional second half day practical workshop using R.

This course is delivered by the Centre for Applied Statistics Courses (CASC) - part of the UCL Great Ormond Street Institute of Child Health (ICH).

Course content

The course will cover the following topics:

  • 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

On the optional second day, you'll put the theory into practice using R (Rstudio) and real-world datasets.

Eligibility

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

To attend the workshop you should have a basic knowledge of R programming.

Learning outcomes

By the end of this course you should be able to:

  • understand the main principles and objectives of meta-analysis
  • pick out relevant data from journal articles for a meta-analysis and calculate summary statistics
  • undertake a fixed effect and random-effects meta-analysis
  • investigate the differences between the studies and how this may impact the study results
  • investigate bias in a meta-analysis

Certificates

You can request a certificate of attendance for this course once you've completed it. Please send your request to ich.statscou@ucl.ac.uk

Include the following in your email:

  • the name of the completed course for which you'd like a certificate
  • how you'd like your name presented on the certificate (if the name/format differs from the details you gave during registration)

Cost and concessions

The fees are as follows:

  • External delegates (non UCL) - £150 (£225 for both days)
  • UCL staff, students, alumni - £75* (£112.50 for both days)
  • ICH/GOSH staff and students - free    

* valid UCL email address and/or UCL alumni number required upon registration

Prices include printed course materials, refreshments (and lunch for non-ICH participants) 12:45pm - 1:45pm.

Cancellations

You can cancel your booking up to five working days before the start of the course for a full refund, but please give as much notice as possible. Places cancelled or changed after this point won't be eligible for a refund. Please send all cancellation requests to the course administrator

Find out about other CASC statistics courses

CASC's stats courses are for anyone requiring an understanding of research methodology and statistical analyses. The courses will 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, and the continuing statistics training scheme (book six one-day courses and get a seventh free.)

Sign up for short course announcements: Subscribe to the UCL Life Learning newsletter to receive news and updates on courses in your chosen area. (For updates on a specific course, contact the administrator - see 'Contact information'.)

Course team

Dr Dean Langan - Course Lead

Dean joined GOS ICH in 2015 as a Teaching Fellow in CASC. 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: 07 Mar 2019, 16:35

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