Introduction to Epidemiological Methods

Overview
Epidemiology historically involved the study of factors associated with communicable disease in a population.  The topic has a long history and is now one of the cornerstones of public health, guiding policy and management of communicable as well as non-communicable diseases.
This course will explain the main types of epidemiological investigations upon which assessments are made, such as cohort and case-control studies.  The relative merits and disadvantages of such designs will be discussed from a practical viewpoint.
The statistical analysis of epidemiological data will be introduced, with the main focus on a binary outcome (diseased or not diseased), and how disease status may be associated with potential risk factors.  Statistical analyses will be performed using the statistical package Stata.  The emphasis will be on practical application and interpretation rather than theory.  A large component of the course will be PC-based practical work.

Who Should Attend?
Medical or public health professionals who already have some statistical training, but whose knowledge is lacking in the area of statistical models specifically for epidemiology.  Prior attendance on A Review of Basic Statistics, or equivalent knowledge, is required for this course.  No prior knowledge of the Stata statistical package is assumed.

How You Will Benefit
You will be introduced to the main types of study design used in epidemiology, and learn how to perform and interpret simple statistical analyses of data from such studies.

What Do We Cover?
  • Epidemiology and public health
  • Study designs: cohort, case-control, matched case-control, cross-sectional and their advantages and disadvantages
  • Effect measures: risk difference, relative risk and odds ratio
  • Introduction to the Stata statistical software package
  • Statistical analysis techniques: confidence interval estimation, hypothesis testing for simple 2x2 tables corresponding to a particular study design
  • Concepts of confounding and interaction (effect modification)
  • Adjusting for confounding factors: stratified analyses 2x2xk tables and Mantel-Haenszel estimators



Available Software
This course has practical exercises written for: Stata
Note: For practical work participants must bring their own laptop with a fully licensed version of the software.

Extra Information
Guest Presenters: Professor Dankmar Böhning of the School of Mathematics, University of Southampton will be one of the course presenters.
Related Courses: Statistical Modelling in Epidemiology
Course Dates
Next run to be announced

Duration: 3 days
Price: £TBC

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