MAS361 Medical Statistics

Note: This is an old module occurrence.

You may wish to visit the module list for information on current teaching.

Both semesters, 2014/15 10 Credits
Lecturer: Dr Eleanor Stillman uses MOLE Timetable Reading List
Aims Outcomes Assessment Full Syllabus

This course comprises sections on Clinical Trials and Survival Data Analysis. The special ethical and regulatory constraints involved in experimentation on human subjects mean that Clinical Trials have developed their own distinct methodology. Students will, however, recognise many fundamentals from mainstream statistical theory. The course aims to discuss the ethical issues involved and to introduce the specialist methods required. Prediction of survival times or comparisons of survival patterns between different treatments are examples of paramount importance in medical statistics. The aim of this course is to provide a flavour of the statistical methodology developed specifically for such problems, especially with regard to the handling of censored data (e.g., patients still alive at the close of the study). Demonstrating implementation of the statistical analyses in the R package is an important part of the course.

NB The teaching is mainly in semester 1, but revision sessions will be held towards the end of semester 2 and the exam in the semester 2 examination period.

Prerequisites: MAS205 (Statistics Core); MAS273 (Statistical Modelling) recommended
Not with: MAS461 (Medical Statistics)
No other modules have this module as a prerequisite.


Outline syllabus

Clinical Trials:
  • Basic concepts and designs: controlled and uncontrolled clinical trials; historical controls; protocol; placebo; randomisation; blind and double blind trials; ethical issues; protocol deviations.
  • Size of trials.
  • Multiplicity and meta-analysis: interim analyses; multi-centre trials; combining trials.
  • Cross-over trials.
  • Binary response data: logistic regression modelling; McNemar's test, relative risks, odds ratios.
Survival Data Analysis:
  • Basic concepts: survivor function; hazard function; censoring.
  • Single sample methods: lifetables; Kaplan-Meier survival curve; parametric models.
  • Two sample methods: log-rank test; parametric comparisons.
  • Regression models: inclusion of covariates; Cox's proportional hazards model; parametric and accelerated failure time regression models.



Aims

  • To illustrate applications of statistics within the medical field.
  • To introduce students to some of the distinctive statistical methodologies developed to tackle problems specifically related to clinical trials and the analysis of survival data.

Learning outcomes

  • have some appreciation of the ethical constraints involved in experimentation on human subjects;
  • understand aspects of the nature and design of clinical trials; and be able to offer advice on the design and size of clinical trials;
  • have some expertise in the handling of binary response data through logistic modelling; and be able to construct lifetables and survival curves;
  • be able to compare survival patterns between different treatments and between different risks; and be familiar with proportional hazard models;

17 lectures, 3 tutorials

Assessment

One formal 2 hour written examination. Format: 3 questions from 4.

Full syllabus

Clinical Trials

  • Basic concepts and designs:
    controlled and uncontrolled clinical trials; historical controls; protocol; placebo; randomisation; blind and double blind trials; ethical issues; protocol deviations. (4 sessions)
  • Size of trials:
    (1 session)
  • Multiplicity and meta-analysis:
    interim analyses; multi-centre trials; combining trials. (2 sessions)
  • Cross-over trials:
    (1 session)
  • Binary response data:
    logistic regression modelling; McNemar's test, relative risks, odds ratios. (2 sessions)
Survival Data Analysis
  • Basic concepts:
    survivor function; hazard function; censoring. (1 session)
  • Single sample methods:
    lifetables; Kaplan-Meier survival curve; parametric models. (4 sessions)
  • Two sample methods:
    log-rank test; parametric comparisons. (1 session)
  • Regression models:
    inclusion of covariates; Cox's proportional hazards model; parametric and accelerated failure time regression models. (4 sessions)
  • Cross-over trials: further aspects (Inter-semester reading)

Reading list

Type Author(s) Title Library Blackwells Amazon
A Everitt and Rabe-Heskith Analyzing Medical Data Using S-Plus 610.285 (E) Blackwells Amazon
A Matthews An Introduction to Randomized Controlled Clinical Trials 615.50724 (M) Blackwells Amazon
B Altman Practical Statistics for Medical Research 519.023 (A) Blackwells Amazon
B Campbell Statistics at Square Two 519.023 (C) Blackwells Amazon
B Collett Modelling Survival Data in Medical Research 610.727 (C) Blackwells Amazon

(A = essential, B = recommended, C = background.)

Most books on reading lists should also be available from the Blackwells shop on Mappin Street.

Timetable (semester 1)

Tue 09:00 - 09:50 lecture   Hicks Lecture Theatre 2
Thu 10:00 - 10:50 lecture   Hicks Lecture Theatre 2