Introduction to Systematic Reviews and Meta-analysis
An online short course
This course aims to introduce participants to the methodology of systematic reviews and meta-analysis.
|Course dates||Due to demand this standalone course will run twice:
29 March - 1 April 2021
13 - 16 July 2021
|Course Organisers||Professor Julian Higgins, Dr Hayley Jones & Dr Jelena Savović|
Please ensure you meet the following prerequisites before booking:
|Knowledge||Participants should have knowledge of statistical methods to the level of our Introduction to Statistics course. A basic appreciation of research designs (to the level of our Introduction to Epidemiology course) would be helpful. Practical session will include implementation of meta-analysis methods in computer software, and either basic knowledge of Stata or familiarity with R would be helpful for this. Students without experience in either will undertake practicals using Stata, and they must have this installed before the start of the course.|
|Software||Participants must either (i) have access to a computer on which Stata* is pre-installed (version 15 or later) OR (ii) be a regular R user.
*Internal University of Bristol participants will be provided with access to Stata v16 on the first day of the course.
This 4-day course will be online and consist of a mixture of live and pre-recorded lectures, with exercises for participants to complete themselves and tutor-facilitated small group sessions. It is full time over the four days.
By the end of the course participants should be able to:
- explain the need for systematic reviews and meta-analyses;
- list the important aspects of a systematic review;
- perform a comprehensive search for relevant literature;
- appreciate the role of tools to assess risk of bias, including their application to randomised controlled trials;
- explain the basic methods of meta-analysis;
- use Stata or R software to perform a basic meta-analysis;
- describe issues in conducting systematic reviews of observational studies;
- summarise the findings of a systematic review or meta-analysis;
- evaluate the quality of a systematic review.
Who the course is intended for
This course is designed for clinicians, researchers, public health specialists and other health care professionals who want to perform and/or evaluate systematic reviews and meta-analyses. The course predominantly focuses on systematic reviews of healthcare interventions, although much of the material translates to systematic reviews in other areas. Sessions examine issues in systematic reviews and meta-analyses of observational studies.
Participants should have knowledge of statistical methods to the level of our Introduction to Statistics course. A basic appreciation of research designs (to the level of our Introduction to Epidemiology course) would be helpful. Practical session will include implementation of meta-analysis methods in computer software, and either basic knowledge of Stata or familiarity with R would be helpful for this. Students without experience in either will undertake practicals using Stata, and they must have this installed before the start of the course.
- Why we need systematic reviews and meta-analyses.
- The systematic review process.
- Identifying relevant studies.
- Selecting studies and data extraction.
- Types of data and effect sizes.
- Assessing risk of bias in primary studies.
- Statistical methods for meta-analysis of dichotomous and numerical (continuous) outcomes.
- Explaining heterogeneity: subgroup analysis and meta-regression.
- Meta-analysis and meta-regression in Stata or R.
- Understanding, investigating and dealing with bias in systematic reviews.
- Systematic reviews and meta-analysis of observational studies.
- Assessing certainty of the evidence in a systematic review.
- Reporting a systematic review.
- Critical appraisal of a systematic review.
Online Course Bookings
Bookings are open for online courses running in 2021.
Find out more
We may need to make responsive changes to our courses at short notice in order to follow the latest Public Health, Government and University guidance on coronavirus (COVID-19).