Epidemiological Methods

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Students should be able to anticipate particular problems that may arise in epidemiological data
• Students should be able to apply appropriate statistical analysis techniques to analyse epidemiological data
• Students should be aware of the effects that chance, confounding and bias may have on epidemiological studies
• Students should be able to distinguish between different types of study design

Lecture 1 – Introduction to Epidemiology

Definition of epidemiology

Basic epidemiological concepts

Epidemiological study design

Developmental Origins of Health and Disease (DOHaD)

Lecture 2 – Bias, Confounding and Interactions

The role of chance

Types of bias

The concept of confounding

Interactions in epidemiological research

Lecture 3 – Establishing causality

Defining causes of disease

How to draw and interpret causal diagrams

Using DAGitty

The Bradford Hill criteria

Lecture 4 – Ratio Measures of Association

Defining risks

Prevalence and incidence

Measures of association

When not to use an odds ratio

Lecture 5 – Case-control studies 1

Design of case-control studies

Design issues

Choice of cases and controls

Matching

Collection of exposure information

Basic analysis of unmatched studies

Test for homogeneity of odds ratios

Mantel-Haenszel methods for stratified analysis

2xk tables

Test for trend

Basic analysis of matched studies

Lecture 6 – Case-control studies 2

Logistic regression - unconditional and conditional

Example of analysis using Stata

Lecture 7 – Cohort Studies 1

Retrospective and prospective cohort studies

Follow-up using official statistics

Analyses using an external standard

Calculating Standardised Mortality Ratios (SMRs)

Lecture 8 – Cohort Studies 2

Poisson generalised linear models to test for trend in SMRs

Cox Proportional Hazards model

Lecture 9 – Design of Epidemiological Studies

A practical session to design a study to assess whether use of mobile phones increases the risk of brain cancer.

Lecture 10 – Ecological Studies and Meta-analysis

Definition of ecological studies

Ecological fallacy

Types of ecological studies

Definition of meta-analysis

Conducting a meta-analysis

Fixed and random-effects models

Forest plots

Lecture 11 – Hints and Tips

Data cleaning

Missing data

Categorisation of continuous variables

Significance testing

Transforming data

Presentation of results

Lecture 12 – Case Study

A practical session discussing an investigation into a cluster of leukaemias near the Sellafield nuclear site in West Cumbria

Learning is through twelve 45 minute lectures and a two-hour Stata tutorial.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.