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MSc Medical Statistics

This course aims to train students from a variety of academic backgrounds to work as statisticians in various sectors including higher education, research institutions, the pharmaceutical industry, central government and national health services. It provides a training in the theory and practice of statistics with special reference to clinical trials, epidemiology and clinical or laboratory research for improved global health.

Graduates from this course pursue careers in medical and epidemiological research, in academic institutions, hospitals, the pharmaceutical industry and various governmental institutions.

The Medical Research Council, Wellcome, GlaxoSmithKline and Amgen offer studentships to UK and EU students. These are advertised each year with the School scholarships information.

Postgraduate Training Fellowship in Medical Statistics for an African Scientist. This fellowship, which is funded by the UK Medical Research Council (MRC), provides support for two years training in medical statistics; during the first year (beginning October 2010) the successful applicant will study for the MSc degree in Medical Statistics at the LSHTM.

The PSI Andrew Hewett Prize is founded in memory of Andrew Hewett, an alumni of LSHTM and awarded by the PSI (Statisticians in the Pharmaceutical Industry) to the best student on the course.

Objectives

By the end of this course students should be able to: select appropriate study designs to address questions of medical relevance; select and apply appropriate statistical techniques for managing common types of medical data; use various software packages for statistical analysis and data management; interpret the results of statistical analyses and critically evaluate the use of statistics in the medical literature; communicate effectively with statisticians and the wider medical community, in writing and orally through presentation of results of statistical analyses; explore current and anticipated developments in medical statistics.

Programme specifications - showing which of the various elements of the Course support and achieve each of these specific Objectives.

Term 1

Students take the following modules: Foundations of Medical Statistics; Introduction to Stata and SAS; Clinical Trials; Basic Epidemiology; Robust Statistical Methods.

Term 1 Module details (PDF 165K)

Terms 2 and 3

Students take a total of six modules, one from each timetable slot. A typical selection of modules is given below, not all modules will be available in any one year. Some modules, shown in italics below, can be taken only after consultation with the Course Director.

C1: Generalised Linear Model

C2: Statistical Methods in Epidemiology.

D1: Survival Analysis and Bayesian Statistics.

D2: Analysis of Hierarchical and Other Dependent Data; Epidemiology & Control of Communicable Diseases.

Term 2 Module details (PDF 212K)

E1: AIDS; Advanced Bayesian Statistics; Epidemiology & Control of Non-Communicable Diseases.

E2: Advanced Statistical Modelling; Advanced Statistical Methods in Epidemiology; Control & Epidemiology of Malaria.

Term 3 Module details (PDF 109K)

Project Report

Students complete a research project usually consisting of analysing a set of data and writing a report, but methodological research can also be undertaken.

Course Duration

Full-time for one year or part-time over two years. Part-time students attend the school on Mondays and Tuesdays during the first year and on Thursdays and Fridays during the second year.

Entrance Requirements

Either a Second-class Honours degree of a recognised university in science, or a related subject, or a degree in medicine. Applicants with an appropriate technical qualification and work experience, or equivalent qualifications, are also welcomed. The course is aimed primarily at graduates with a mathematically-based first degree which includes some statistics. Graduates from other fields who have quantitative skills and some familiarity with statistical ideas may also apply.

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Student profile

Good lecturers, quality teaching, provision of in-depth course notes and a lot of support make this a really excellent course.

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Neville Calleja

Robyn Drake from New Zealand studied for MSc Medical Statistics