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The University of Southampton
Southampton Statistical Sciences Research Institute

Advanced Statistical Methods in Epidemiology

This three-day course is aimed at academic researchers in the medical and health or social sciences or who may work in government, the pharmaceutical industry, or other parts of the private sector who want to perform statistical modelling and analysis of epidemiological study data.

Individual day(s) are available on request, please email  who will happy to advise. 

Course Code S3RIASME
Course Dates 18th April 2018 – 20th April 2018
Course Leader Professor Dankmar Boehning

Course Description
Topics will include the basic disease occurrence measures of prevalence and incidence with their role in surveillance including standardization, Mantel-Haenszel estimation of various effect measures including the risk ratio and risk difference for cohort studies and the odds ratio for case-control studies as well as Poisson and logistic regression to adjust for potential confounders simultaneously. 

The course will also include elements of time-to-event analysis including Kaplan-Meier estimation and Cox’ proportional hazards model for confounder adjustment. 

The course will comprise of a mixture of lectures and practical workshops using the software STATA.

Participants are expected to have a good working knowledge of simple statistical methods, including a good understanding of estimation of parameters including confidence intervals, hypothesis testing and p-values.  No familiarity with the software STATA is required.

Supplementary Items 

Registered Students

Staff from academic institutions (including research centres)

For all other participants

University of Southampton - Building 39

Venue Details
University of Southampton,
Southampton Statistical Sciences Research Institute,
Building 39,
SO17 1BJ

Additional Information
The course will be held at the Southampton Statistical Sciences Research Institute, Building 39, University of Southampton, Southampton, SO17 1BJ. Participants will need to make their own accommodation arrangements.

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