# Unit information: Statistics for Epidemiology in 2021/22

Unit name Statistics for Epidemiology BRMSM0032 20 M/7 Teaching Block 2 (weeks 13 - 24) Dr. Jon Heron Not open BRMSM0001: Introduction to Epidemiology and Statistics None Bristol Medical School Faculty of Health Sciences

## Description

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 details

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 Details

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).

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.

## 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).