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 Review Manager and Stata software.
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 22nd February 2019. 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 three different software packages (Stata, Review Manager and R) to perform meta-analysis
- Use methods to explore heterogeneity and appropriately use fixed and random effects, subgroup analysis, sensitivity analysis and meta-regression
- Carry out and interpret cumulative meta-analysis, 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
- Cumulative meta-analysis
- Diagnostic accuracy meta-analysis in Stata and RevMan
- Introduction to meta-analysis using ‘R’ statistical package
- 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 is run over an eight week cycle where the first week is spent working on introductory activities using a Virtual Learning Environment, the second week is spent in Oxford for the face to face teaching week (this takes place on the dates advertised), there are then four Post-Oxford activities (delivered through the VLE) 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).
Accommodation is available at the Rewley House Residential Centre, within the Department for Continuing Education, in central Oxford. The comfortable, en-suite, study-bedrooms have been rated as 4-Star Campus accommodation under the Quality In Tourism scheme, and come with tea- and coffee-making facilities, free Wi-Fi access and Freeview TV. Guests can take advantage of the excellent dining facilities and common room bar, where they may relax and network with others on the programme.
Please ensure that you have access to a computer that meets the specifications detailed on our technical support page.
Short Course in Health Sciences: £2285.00
Students enrolled on MSc in Evidence-Based Health Care: £1850.00
Students enrolled on Postgraduate Cert in Health Research: £1850.00
Students enrolled on Postgraduate Dip in Health Research: £1850.00
Details of funding opportunities, including grants, bursaries, loans, scholarships and benefit information are available on our financial assistance page.
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.
Jenny Hirst is an NIHR Doctoral Research Fellow at the Nuffield Department of Primary Care Health Sciences. The primary focus of her research is on diabetes.
Assessment will be based on submission of a written assignment which should not exceed 4,000 words.
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 firstname.lastname@example.org if you have any questions.
We strongly recommend that you download and save files before completing to ensure that all your changes are saved.
This course requires you to complete the application form and submit along with a copy of your CV. If you are applying to take this course for academic credit you will also need to complete section two of the reference form and forward it to your referee for completion. 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 before completing the application form, as any errors resulting from failure to do so may delay your application.
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.
Terms and conditions
Terms and conditions for applicants and students on this course
Sources of funding
Information on financial support