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Overview
Overview - Advanced Statistical Methods in Epidemiology
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The overall module aim is to enable students to understand, apply and interpret the results of a range of advanced techniques for the design and analysis of epidemiological studies.

Intended learning outcomes

Upon successful completion of the module, a student should be able to:

  • Select, apply and interpret regression methods for the analysis of case-control and cohort studies using appropriate computer software.
  • Understand when individual observations are not independent and how to account for this using appropriate statistical methods.
  • Plan a strategy of analysis for an epidemiological dataset, using an appropriate choice of statistical methods. 
  • Write a clear report presenting and interpreting the results of an analysis of epidemiological data.

Session Content

The module is expected to cover the following topics:

Regression methods for case-control studies: 

  • Unconditional and conditional logistic regression.

Regression methods for cohort studies and survival analysis: 

  • Stratifying on time.
  • Poisson regression.
  • Cox regression.
  • Further issues in the analysis of cohort studies.

Analysis of correlated data: 

  • Random effects models.
  • Generalised estimating equations. 
  • Design and analysis of cluster-randomised trials.

Miscellaneous topics: 

  • Causal diagrams.
  • Attributable fractions. 
  • Additive and multiplicative models. 
  • Analysis of quantitative data. 
  • Missing data. 
  • Strategies of analysis.

Mode of delivery

This module is delivered predominantly face-to-face. Where specific teaching methods (lectures, seminars, discussion groups) are noted in this module specification these will be delivered by predominantly face-to-face sessions. There will be a combination of live and interactive activities (synchronous learning) as well as self-directed study (asynchronous learning).

Assessment

For their summative assessment, students are asked to prepare a report on their analysis of an epidemiological dataset. Work on the analysis and preparation of the report continues throughout the module. Students are provided with an epidemiological dataset and questions to guide them through the analysis. They are asked to analyse the dataset to address the research questions and to prepare a report describing their detailed analysis strategy, the results they obtained, and provide a discussion and interpretation of their results. 

The assessment task requires students to identify an appropriate strategy to analyse the dataset and to select and apply appropriate statistical methods to address the questions raised. The students will need to present their analysis strategy and results appropriately and be able to interpret their findings in the light of the study design and research question. 

The assessment provides students with the opportunity to apply their learning across the module as well as to consolidate their statistical learning across the year and to gain confidence to undertake their own analysis in the future.

Credits

  • CATS: 15
  • ECTS: 7.5

Module specification

For full information regarding this module please see the module specification.

Entry requirements
Entry requirements - Advanced Statistical Methods in Epidemiology
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This is an advanced module intended for students with a strong grasp of quantitative methods, who have successfully completed the module in Statistical Methods in Epidemiology (2402 or EPM202).

How to apply
How to apply - E
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Applications for Term 3 E modules are currently open and will close on Tuesday 1 April 2025. Applications should be made online via our application portal.