Meta-analysis

Overview

Basic and advanced statistical methods for meta-analysis

The Meta-analysis short course for health professionals is designed to provide an overview of different meta-analysis methods and common problems encountered with extracting data. Basic and advanced methods which can be used to combine data from various study types will be covered using statistical software such as R and Stata.

Topics covered will include standard methods for intervention comparisons, approaches which can be used for combining different summary measures, subgroup analyses and methods to investigate heterogeneity, as well as advanced methods for diagnostic accuracy, individual patient data and network meta-analysis.

The last date for receipt of complete applications is 5pm Friday 7 March 2025. Regrettably, late applications cannot be accepted.

The overall aims of this module are to enable students to:

  • Be able to plan, carry out and interpret meta-analysis of different study designs for questions in evidence based healthcare.
  • Extract data in different formats and deal with missing data
  • Use statistical software to perform meta-analysis (such as Stata or R)
  • Use methods to explore heterogeneity and appropriately use fixed and random effects, subgroup analysis, sensitivity analysis and meta-regression
  • Carry out and interpret diagnostic accuracy meta-analysis and network meta-analysis
  • Understand the advantages and limitations of an individual patient data meta-analysis

 

The course will cover the following topics:

  • Introduction to different meta-analysis methods and the advantages or disadvantages of each
  • Common problems encountered with data extraction
  • Heterogeneity, fixed and random effects, meta-regression, unit of analysis, follow-up and cross-over studies
  • Approaches to meta-analysis of different study designs
  • Diagnostic accuracy meta-analysis
  • Introduction to meta-analysis using statistical software (such as Stata and R)
  • Network meta-analysis
  • Introduction to individual patient data meta-analysis

Teaching will include a combination of presentations by tutors, full group and small group practical sessions.

This module assumes the students have at least some familiarity with the following:

  • Distinction between continuous and categorical variables
  • Interpretation of p values and statistical significance
  • Interpretation of confidence intervals
  • Concept of the Normal distribution
  • Risk ratio, odds ratio and linear and logistic regression

If you do not have these pre-requisites, the online module Introduction to Statistics for Health Care Research is recommended.

Programme details

This module is run over an eight week cycle using a Virtual Learning Environment, where the first week is spent working on introductory activities, the second week is a full week of online teaching (this takes place on the dates advertised), there are then four weeks of self-directed activities which are designed to help you write your assignment. You then have a week of personal study and you will be required to submit your assignment electronically the following week (usually on a Tuesday at 14:00 UK Local Time).

 

Fees

Description Costs
Short Course in Health Sciences £3175.00
Students enrolled on MSc in EBHC £2570.00

Funding

Details of funding opportunities, including grants, bursaries, loans, scholarships and benefit information are available on our financial assistance page.

Discounts

If you are an employee of the University of Oxford and have a valid University staff card you may be eligible to receive a 10% discount on the full stand-alone fee. To take advantages of this offer please submit a scan/photocopy of your staff card along with your application. Your card should be valid for a further six months after attending the course.

Tutors

Dr José Ordóñez-Mena

Module Co-ordinator

José Ordóñez-Mena is a Senior Medical Statistician at the Nuffield Department of Primary Care Health Sciences, University of Oxford.

Dr Kathy Taylor

Module Co-ordinator

Dr Kathy Taylor is a Medical Statistician at the Nuffield Department of Primary Care Health Sciences, University of Oxford.

Assessment methods

Assessment will be based on submission of a written assignment which should not exceed 4,000 words.

Academic Credit

Applicants may take this course for academic credit. The University of Oxford Department for Continuing Education offers Credit Accumulation and Transfer Scheme (CATS) points for this course. Participants attending at least 80% of the taught course and successfully completing assessed assignments are eligible to earn credit equivalent to 20 CATS points which may be counted towards a postgraduate qualification.

Applicants can choose not to take the course for academic credit and will therefore not be eligible to undertake the academic assignment offered to students taking the course for credit. Applicants cannot receive CATS (Credit Accumulation and Transfer Scheme) points or equivalence. Credit cannot be attributed retrospectively. CATS accreditation is required if you wish for the course to count towards a further qualification in the future.

A Certificate of Completion is issued at the end of the course.

Applicants registered to attend ‘not for credit’ who subsequently wish to register for academic credit and complete the assignment are required to submit additional information, which must be received one calendar month in advance of the course start date. Please contact us for more details.

Please contact cpdhealth@conted.ox.ac.uk if you have any questions.

Application

This course requires you to complete the application form and to attach a copy of your CV. If you are applying to take this course for academic credit you will also be required to provide a reference. Please note that if you are not applying to take the course for academic credit then you do not need to submit a reference.

Please ensure you read the guidance notes which appear when you click on the symbols as you progress through the application form, as any errors resulting from failure to do so may delay your application.

Selection criteria

Admissions Criteria:
To apply for the course you should:

  • Be a graduate or have successfully completed a professional training course
  • Have professional work experience in the health service or a health-related field
  • Be able to combine intensive classroom learning with the application of the principles and practices of evidence-based health care within the work place
  • Have a good working knowledge of email, internet, word processing and Windows applications (for communications with course members, course team and administration)
  • Show evidence of the ability to commit time to study and an employer's commitment to make time available to study, complete course work and attend course and university events and modules.
  • Show evidence of your previous statistical knowledge.
  • Be able to demonstrate English Language proficiency at the University’s higher level

IT requirements

Please ensure that you have access to a computer that meets the specifications detailed on our technical support page.