Unit information: Statistics for Epidemiology in 2020/21

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	BRMSM0001: Introduction to Epidemiology and Statistics
Co-requisites	None
School/department	Bristol Medical School
Faculty	Faculty of Health Sciences

Description including Unit Aims

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 missing data, and introduce methods to address these

Intended Learning Outcomes

By the end of this unit, students should be able to:

1. Use statistical software to manipulate, describe and analyse data
2. Conduct analyses using appropriate regression models, considering study design, type of outcome variable and potential confounders
3. Interpret the results from regression models of epidemiological data, considering study design issues
4. Use regression models to adjust for confounding, test for effect modification and model linear and nonlinear relationships
5. Conduct statistical analyses for time-to-event outcomes
6. Construct, validate and interpret prediction models for diagnosis and prognosis

Teaching Information

Teaching will include learning activities set by the tutor including lectures (synchronous and asynchronous), small group work, discussions, individual tasks, and practical activities (face to face or online).

Directed and self-directed learning will include activities such as reading, accessing web-based supplementary materials, critical analysis and completion of assessments

Assessment Information

Formative assessment: Practical session on constructing and validating a risk prediction model .

Summative assessment: The unit will be assessed using a single piece of coursework:

• Data analysis and interpretation exercise. Students will be given a data set and a set of analytical 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 1-6; 100% of total unit mark).

A mark of 50% is required to pass the unit.

Reading and References

There is no essential unit text book.

Recommended reading:

1. Kirkwood BR, Sterne JAC. (2010) Essential Medical Statistics. Blackwell.
2. Sterne, JAC et al. (2009). Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ 338:157-160.
3. Cleeves M, Gould W, Gutierrez R, Marchenko Y. An Introduction to Survival Analysis Using Stata, 3^rd edition. Stata Press 2010.