Unit information: Statistics for Epidemiology in 2021/22

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, small group work, discussions, individual tasks, and practical activities.

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:

Formative assessments will come in many forms such informal questioning, quizzes and group exercises in lectures, tutorials and homework. These form an assessment for learning and will not contribute to the final unit mark. Stata-based elements will be a feature of the majority of the practical sessions, including the one-day prediction “workshop” where students will work (and compete) in teams in an attempt to devise the best prediction model.

Summative assessment:

The unit will be assessed using three pieces of coursework. Each will consist of a data analysis and interpretation task. Students will be given a data set and a set of analytical tasks to complete:

Linear and logistic regression (ILO 1-4; 33.3% of total unit mark)
Time to event models (ILOs 1-5; 33.3% of unit mark)
Prediction modelling (ILOs 1, 6; 33.3% of unit mark)

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

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. BRMSM0032).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.