PHPS41110 Advanced Epidemiology

Academic Year 2022/2023

The purpose of this module is to build on the epidemiological knowledge and skills acquired in a basic epidemiology course such as PHPS40010 (Principles of Epidemiology). Students will learn the impact of bias, confounding and effect modification on efforts to establish causation in epidemiological and clinical studies. They will examine the concept of causal inference and causal pathways. They will explore reasons for, and impact of, missing data on analysis and interpretation of results. They will learn about analytical methods used to adjust for missing data and examine datasets with missing data. There will be a particular emphasis on the design of measurement instruments for both objective assessment and subjective reporting of health, disease and disability. This will include the definition of endpoints and outcomes of interest and the assessment of the properties of instruments used to ascertain endpoints and outcomes. They will learn and practice analysis of categorical data using factor analysis and methods of cluster analysis. They will be oriented to emerging fields of importance in epidemiology such as disease modelling and projection, and genomic analysis to understand patterns and dynamics of disease transmission and networks.

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Curricular information is subject to change

Learning Outcomes:

Students will:
- be able to design epidemiological and clinical studies with a thorough understanding of the potential biases to be considered and avoided if possible;
- know how to control, in so far as possible, for confounding and effect modification by collecting data on possible confounding and effect modifying variables;
- have the capability to design study and data collection instruments and assess their validity, reliability and other properties;
- understand different types of study endpoints and the importance of standardised and agreed definitions;
- know how to develop and interpret composite score and latent variables;
- understand the impact of missing data and the techniques which can be used for imputation;
- carry out data reduction techniques and cluster analysis using SPSS, and interpret results;
- understand the purpose, assumptions and implementation of disease modelling;
- be aware of the contributions of basic sciences and genomic analyses in unravelling transmission patterns and dynamics.

Indicative Module Content:

Bias, confounding, effect modification and chance
Techniques in study design to control for bias and confounding
Analytical techniques to control for confounding and assess effect modification
Causal inference and pathways
Reasons for, impact of, and techniques for imputation of missing data
Design and assessment of measurement instruments and PROMS;
Techniques for data reduction and extraction
Cluster analysis using SPSS

Student Effort Hours: 
Student Effort Type Hours
Lectures

12

Seminar (or Webinar)

6

Specified Learning Activities

20

Autonomous Student Learning

60

Online Learning

12

Total

110

Approaches to Teaching and Learning:
Lectures in-person and online, as required
Critical review of relevant published work
Group work and learning
Practical assignments using appropriate software
 
Requirements, Exclusions and Recommendations
Learning Requirements:

PHPS40010 or equivalent


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Structured report: Analysis of a dataset provided using one of the techniques covered in the module. Coursework (End of Trimester) n/a Standard conversion grade scale 40% Yes

65

Class Test: Quiz: Appropriate analysis of PROM and QOL data Throughout the Trimester n/a Standard conversion grade scale 40% No

10

Group Project: Group presentation: Assessment of the properties of measurement instruments. Throughout the Trimester n/a Standard conversion grade scale 40% Yes

25


Carry forward of passed components
Yes
 
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Mr John Loughrey Tutor
Dr Guerrino Macori Tutor