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Longitudinal Data Analysis

Course Description

The aim of the course is to provide an introduction to and hands on experience of the analysis longitudinal studies using: 

  • Random effects models for continuous outcome
  • Growth curve models
  • GEE models for continuous outcomes
  • Random effects models for binary data
  • GEE models for binary data
  • Event history

The course will comprise 8 lectures of one hour length and 7 practicals of 90 minutes length, with tea breaks!  

Pre-requisites are: 

  • Experience of STATA or similar package
  • Experience of linear and logistic regression
  • Experience of data analysis

Detailed timetable is available here.

For more information  please contact the course organiser, Owen Nicholas.

Researcher Development Framework Categories

A1) Knowledge base

Course Recommended for

This course is particularly relevant to the following groups:

  • Students in Social & Historical Sciences
  • Students in Medical Sciences
  • Students in Population Health Sciences

Course Organisers

  • Course Director - Prof Jenny Head - (Research Department of Epidemiology & Public Health)
  • Organiser - Dr Owen Nicholas - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Dr Mai Stafford - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Prof Amanda Sacker - (Research Department of Epidemiology & Public Health)
  • Administrator - Ms Kasia Bronk - (Organisational & Staff Development)

 

4-7 Nov 2014 expand

Page last updated: 22nd July 2010