This module is the second of two Applied Statistics for Infectious Disease Epidemiology modules that will provide training in statistical methods and their...

Applied Statistics for Infectious Disease Epidemiology 2 (GLBH0048)

This module is the second of two Applied Statistics for Infectious Disease Epidemiology modules that will provide training in statistical methods and their application to address research questions focused on infectious disease problems. Students will apply concepts in practical sessions, in which they will learn to use statistical software and to critically appraise the methods that they are applying, and interpret results in the context of infectious disease epi knowledge developed through other core and optional modules. 

This module will build on core statistical concepts to focus on more advanced skills in data manipulation and analysis. This will include methods to explore associations with count outcomes, analyse time-to-event data in determining the risk of an event, and understand the complexities of modelling correlated outcomes. It will also cover how to evaluate and manage missing data, conduct sensitivity analyses to evaluate the impact of model assumptions, and build and validate risk prediction models among other topics.

At the end of this module, students will be able to discuss, plan and execute analyses aimed at effectively addressing a specific ID epi research question taking into account limitations of observational data, and to interpret and appraise the results of statistical analyses they encounter in the literature.
 

This module is the first of two Applied Statistics for Infectious Disease Epidemiology modules that will provide training in statistical methods and their...

Applied Statistics for Infectious Disease Epidemiology 1 (GLBH0047)

This module is the first of two Applied Statistics for Infectious Disease Epidemiology modules that will provide training in statistical methods and their application to address research questions focused on infectious disease problems. Students will apply concepts in practical sessions, in which they will learn to use statistical software and to critically appraise the methods that they are applying, and interpret results in the context of infectious disease knowledge developed through other core modules.

This module will develop practical skills in understanding a dataset and preparing it for analysis, along with approaches to displaying and describing data. The module will introduce core statistical concepts of sampling, summary measures and confidence intervals, hypothesis testing and the characteristics of probability distributions. The module will also introduce the use of regression models for continuous and binary outcomes, and explore the interpretation of such models when fitted to real datasets. Material on bias, confounding and effect modification will be closely integrated with epidemiology teaching in other modules.

The applied focus of this module will situate the techniques covered within the need to make reasoned decisions about analysis of a dataset to answer an ID epi question, whilst making critical judgements regarding data quality and the interpretation of analyses performed. The module will also cover the effective presentation of results for dissemination.

Readings from this module will include:

Essential Medical Statistics by Kirkwood and Sterne (2nd edition, Blackwell Science)
	Medical Statistics at a Glance by Petrie and Sabin (4th Ed, Wiley Blackwell)