HAR6170: Medical Statistics and Evidence Synthesis

Module description

This module introduces students to key concepts and methods used in medical statistics.

The module is organised in two parts:

• Design, analysis and reporting of randomised control trials.
• Synthesis of evidence from multiple clinical trials using meta-analysis methods and quantifying uncertainty using experts’ beliefs.

Classical (ie frequentist) and Bayesian meta-analysis methods will be presented with an emphasis on how evidence can be used to represent uncertainty about input parameters in decision analytical models.

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Objectives

On satisfactory completion of the course, a student will be able to:

• Describe the process of setting and testing statistical hypotheses in randomised controlled trials
• Describe and apply appropriate Classical statistical methods for analysing different types of data collected in randomised controlled trials
• Conduct Classical analyses of data collected in randomised controlled trials using statistical software
• Describe the Bayesian approach to statistics and contrast it with the Classical approach
• Describe what is meant by fixed effect and random effects models for meta-analysing evidence from multiple randomised controlled trials
• Describe what is meant by a standard pairwise meta-analysis and a network meta-analysis of evidence from multiple randomised controlled trials, and be able to conduct a Bayesian analysis using appropriate statistical software
• Describe the process of the elicitation of experts’ beliefs

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Teaching

This module can also be taken as part of the following courses:

This module is available as a DDP module

Informal lectures, some of which will include exercises for students to complete, will provide the majority of contact hours with lecturers (10 x 2 hours). For nine weeks, tutorials will be given to undertake computer-based problem-solving (10 x 2 hours).

Study expectations

Students will be expected to undertake approximately 110 hours of independent study, including preparation for tutorials, preparation for assignments and further recommended reading of articles published in peer-reviewed journals and textbooks.

These learning methods will reinforce learning outcomes and provide practical experience in applying some concepts.

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Fees and funding

You can find out more about fees and funding for CPD modules in the School of Medicine and Population Health at the link below. We accept sponsored as well as self-funding students.

Fees and funding information

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How to apply

Find out what you need to do to apply for a CPD module in the School of Medicine and Population Health.

Apply for this module

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Contact

For more information on this module, speak to the lead academic: