Essential Medical Statistics

Overview

Learning about logistic regression, Cox regression, survival analysis and more

This module is designed for health care professionals or graduate students who already have some research experience and an understanding of basic statistical principles, and who wish to develop their statistical expertise. Teaching is interactive and will emphasise the practical application of statistical methods to real-life problems, rather than statistical theory. Students will be able to explore and analyse data using a variety statistical packages.

The last date for receipt of complete applications is 5pm Friday 10th May 2024. Regrettably, late applications cannot be accepted.

This module will cover:

• Hypothesis tests
• Association between variables
• Linear regression
• Multiple linear regression (including relation to ANOVA*)
• Multiple logistic regression
• Uses of multiple logistic regression
• Interpretation
• Interaction
• Building models
• Survival analysis
• Non parametric methods
• Life tables and their application to follow-up studies
• The Kaplan Meier product-limit estimate of survival and the log rank test
• Parametric methods
• The hazard function
• Use of regression and proportional hazards models to assess the association of factors other than time with survival
• Cox regression model

*The terminology of ANOVA has been widely superseded by the terminology of multiple linear regression. The course will show briefly the equivalence of the two approaches for the benefit of students accustomed to ANOVA.

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

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

"Very good presentation of a lot of information, with relevant examples, very good practical sessions and helpful lecturers"

Programme details

This module is run over a thirteen week cycle using a Virtual Learning Environment where the first week is spent working on introductory activities, then there are eight weeks of online teaching (this takes place on the dates advertised), which are designed to help you write your assignment. You then have 4 weeks 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
New students enrolled on MSc in EBHC £2340.00
New students enrolled on PG Dip in Health Research £2340.00
Short Course in Health Sciences £2890.00

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 advantage 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 Susannah Fleming

Module Coordinator

Susannah Fleming is a Senior Quantatitive Researcher at the Nuffield Department for Primary Care Health Sciences, University of Oxford

Dr Megan Kirk Chang

Module Co-ordinator

Megan Kirk Chang is a Senior Researcher at the Nuffield Department for Primary Care Health Sciences, University of Oxford.

Dr Richard Stevens

Module Coordinator

Richard Stevens is Course Director of the MSc in EBHC Medical Statistics, Deputy Director of the Statistics Group at the Centre for Evidence-Based Medicine, Oxford and an Associate Professor.

Assessment methods

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.

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

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.