Back to MMath/MAST in Mathematics Home Page \ Statistics Group Home Page

Biostatistics (L16)

This course consists of two components: Survival Data and Statistics in Medical Practice. Together these make up one 2 unit (16 lecture) course. You must take both components together for the examination. Survival Data has 10 lectures and 2 classes; Statistics in Medical Practice has 6 lectures and 1 class.

Survival Data (L10+2) P. Treasure

6 Lectures on Fundamentals of Survival Analysis

Characteristics of survival data; censoring. Definition and properties of the survival function, hazard and integrated hazard. Examples.

Review of inference using likelihood. Estimation of survival function and hazard both parametrically and non-parametrically.

Explanatory variables: accelerated life and proportional hazards models. Special case of two groups. Model checking using residuals.

4 Lectures on Current Topics in Survival Analysis

In recent years there have been lectures on: frailty, cure, relative survival, empirical likelihood, counting processes and multiple events.

2 Example Classes
Following immediately after the lectures, the example classes apply the lectured material to real survival analysis contexts and datasets.

1 Revison Class (2 hours)
The revision class takes place just before the examination period in the Easter Term.
Principal book
1. D. R. Cox & D. Oakes, Analysis of Survival Data, London: Chapman & Hall (1984).
Other books
2. P. Armitage, J. N. S. Matthews & G. Berry, Statistical Methods in Medical Research (4th ed.), Oxford: Blackwell (2001) [Chapter on Survival Analysis for preliminary reading].
3. M. K. B. Parmar & D. Machin, Survival Analysis: A Practical Approach (1995), Chichester: John Wiley.

Statistics in Medical Practice (L6) S. Bird, R.Turner & I. White

Each lecture will be a self-contained study of a topic in biostatistics, which may include study design (including randomization and evaluation of interventions), meta-analysis, clinical trials, and/or nonrandomized studies, and statistical criticism of published medical papers. The relationship between the medical issue and the appropriate statistical theory will be illustrated.

Appropriate books
There are no appropriate books, but relevant medical papers will be made available beforehand for prior reading. It would be very useful to have some familiarity with media coverage of medical stories involving statistical issues, e.g. from Behind the Headlines on the NHS Choices website: