Unit name | Statistics for Epidemiology |
---|---|
Unit code | BRMSM0032 |
Credit points | 20 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
Unit director | Dr. Jon Heron |
Open unit status | Not open |
Pre-requisites |
Introduction to Epidemiology and Statistics |
Co-requisites |
None |
School/department | Bristol Medical School |
Faculty | Faculty of Health Sciences |
The aims of this unit are to:
- Use statistical software to manage and manipulate data - Conduct statistical analyses of epidemiological data, and interpret their results - Describe statistical methods commonly applied in epidemiology including linear, logistic, Poisson and Cox regression, their extensions to clustered data and random effects, and other methods for survival analysis - Use regression models to adjust for confounding, test for effect modification and model linear and nonlinear relationships - Construct, validate and interpret prediction models to address diagnostic and prognostic research questions - Understand the implications of clustered and missing data, and introduce methods to address these - Understand simulation as a method to aid design, analysis or interpretation of a study - Introduce applications of machine learning in epidemiologyOn successful completion of the unit, students should be able to:
There will be 10 teaching weeks, plus reading week and revision week.
Face to face teaching for a total of 50 hours will include lectures and tutorials. Directed and self-directed learning (150 hours) will include activities such as reading, analysing and interpreting data, and preparation for assessment.
There will be two formative assessments: the first will be a practical session on constructing and validating a risk prediction model (ILO 6). The second formative assessment will be a practical session on using simulation to inform the design of a future study (ILO 8).
Summative assessment will be in the form of a data analysis and interpretation exercise. Students will be given a data set and a set of analysis tasks to complete. They will also be asked to state the strengths and limitations of their analysis and discuss possible alternatives, with suitable justification (ILO 1-9).
A mark of 50% for the summative coursework assessment is required to pass the unit.
There is no compulsory unit text book.
Recommended reading: