BSc Mathematics with Finance

Randomised controlled trials are planned experimental studies on human subjects designed to assess the benefit of medical treatments. Other important areas of application of statistical methods in medical research are epidemiological studies, which investigate the possible causes of disease from observational data, diagnostic studies, which methods of disease diagnosis and meta-analysis, which considers combining information from multiple studies. Many of the major developments in modern statistics have been motivated by problems in medical research. Whilst briefly outlining other areas of application in medical research, the lecture course will introduce the statistical issue associated design and analysis of randomised controlled trials and in meta-analyses.

This course unit introduces the application of statistical ideas and methodology to medical research.

On successful completion of this course unit students will be able to: 

1. Appraise the design, analysis and interpretation of the results of randomised controlled trials (RCTs), with specific reference to minimising bias.
2. Choose, with justification, the design, including calculation of the sample size, for a RCT with a continuous or binary outcome.
3. Analyse data from RCTs of various designs (including: parallel, crossover or cluster; superiority, non-inferiority or equivalence), including the meta-analysis of several RCTs, and interpret the findings in the relevant context.
4. Derive key mathematical expressions with applications to RCTs or meta-analyses of RCTs.

• Introduction to medical statistics. Randomised controlled trials: historical background and ethical issues concerning randomised experimentation on human subjects.
• Design and organisation of randomised controlled trials. Types of bias and methods for controlling bias including blinding and placebo treatments.
• Sample size estimation for continuous and binary outcome measures.
• Methods of treatment allocation including simple randomization, random permuted blocks, stratification and minimization.
• Implications of equivalence and non-inferiority hypotheses for sample size and statistical analyses.
• Statistical methods for the analysis of parallel group trials including methods for the adjustment for baseline data.
• Implications of protocol deviations and the motivation for the intention-to-treat principle.
• Multiplicity issues: sub-group analysis and multiple outcomes.
• Alternatives designs for randomised controlled trials: cross-over trials and cluster randomised trials.
• Meta-analysis and publication bias.

• Coursework: weighting 20%
• End of semester examination: weighting 80%

Feedback tutorials will provide an opportunity for students' work to be discussed and provide feedback on their understanding.  Coursework or in-class tests (where applicable) also provide an opportunity for students to receive feedback.  Students can also get feedback on their understanding directly from the lecturer, for example during the lecturer's office hour.

• Matthews, JNS, An Introduction to Randomized Controlled Clinical Trials, 2nd edition 2006, Chapman & Hall/CRCPress

The first edition (2000) is also adequate for this course and there are copies of both in the John Rylands Library

The independent study hours will normally comprise the following. During each week of the taught part of the semester:

• You will normally have approximately 60-75 minutes of video content. Normally you would spend approximately 2-2.5 hrs per week studying this content independently
• You will normally have exercise or problem sheets, on which you might spend approximately 1.5hrs per week
• There may be other tasks assigned to you on Blackboard, for example short quizzes or short-answer formative exercises
• In some weeks you may be preparing coursework or revising for mid-semester tests

Together with the timetabled classes, you should be spending approximately 6 hours per week on this course unit.

The remaining independent study time comprises revision for and taking the end-of-semester assessment.

The above times are indicative only and may vary depending on the week and the course unit. More information can be found on the course unit’s Blackboard page.