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ST409: Medical Statistics with Advanced Topics

Lecturer(s): Professor Jane Hutton

Availability: Only available to students who have NOT taken ST332.

Commitment: 3 lectures/week. This module runs in Term 2.

Prerequisite(s): ST218/219 Mathematical Statistics A&B

Content: Modern applications of statistics to medicine are highly developed. A look at almost any medical journal reveals that a substantial proportion of medical research papers employ statistical techniques. Large numbers of statisticians are employed in medical research establishments, particularly in the pharmaceutical companies and the medical schools, and medical statistics continues to be the most buoyant area for statistical recruitment. Although the course will cover some topics of a specifically medical nature, much of the work will be discussing basic statistical techniques as applied to medical data, but which could equally well be applied to data arising in other applications. Thus, whilst medicine provides the focus of the course, it could also be viewed as a more general applied statistics course. The course will explain why and how statistics is used in medicine, and study some of the statistical methods commonly used in medical research. Examples and case studies in areas such as cancer, heart disease and psychiatry will be discussed.

  • Generalised linear models: linear models as an extension of linear regression; analysis of binary data by logistic regression; analysis of counts and proportions. Two by two tables.
  • Study designs: cohort, case-control and survey designs; randomised clinical trials; sample size and power; conditioning and covariance adjustment.
  • Analysis of censored survival data: life tables; hazard and survival functions; Kaplan-Meier survival curves; parametric survival models, the proportional hazards regression model.

Aims: To introduce applications of statistics in medicine, and some of the statistical methods commonly used in medical research.


  • To appreciate the role of statistics in medical research.
  • To understand some of the statistical principles of good practice in medical investigations.
  • To understand how to use and interpret some of the statistical techniques used in medical data analysis.


  • A.J. Dobson, “An introduction to generalised linear models”;
  • D.G. Altman, “Practical statistics for medical research”;
  • D. Collett, “Modelling survival data in medical research”. (All Chapman & Hall)

Students will be given selected advanced material for further study and examination.

Assessment: One assignment worth 10%, one group project worth 10%, 80% by examination

Deadline: Individual Assignment - Term 2 Week 6 and Group Project - Term 3 Week 2

Feedback: Feedback will be returned within 20 working days.

You may also wish to see:

ST409: Resources for Current Students
(restricted access)

You may also wish to see:

ST409: Resources for Current Students
(restricted access)