Longitudinal data analysis population average and random effects models Event
- Time:
- 09:30 - 17:00
- Date:
- 30 June 2014 - 2 July 2014
- Venue:
- Southampton Statistical Sciences Research Institute Building 39 University of Southampton Southampton SO17 1BJ Participants are left to book their own accommodation according to individual needs.
For more information regarding this event, please telephone CASS Courses in Applied Social Surveys programme enquiries on +44 (0)23 8059 5376 or email cass@soton.ac.uk .
Event details
This course starts by reviewing the advantages of collecting and analysing longitudinal data.
After discussing the various types of longitudinal data, we focus on panel data containing repeated measures. Topics will include: methods for exploring longitudinal data; alternative approaches for modelling repeated measures data for continuous and categorical responses with particular attention to population average and random effects models; and methods for handling complex survey designs, weights and non-response.
Course Objectives:
- To provide an introduction to various approaches for analysing longitudinal survey data, including methods for handling complex surveys, weights and non-response.
- To enable participants to identify the important issues when analysing longitudinal survey data.
Course Content:
This course will include the following topics:
- Issues when analysing longitudinal survey data
- Overview of approaches to analysing longitudinal survey data
- Population average (marginal) models
- Random effects models
- Methods for categorical responses
- Handling complex survey designs, weights and non-response
The methods will be illustrated and compared using analyses of attitudes and life satisfaction scores collected in the British Household Panel Survey. The course will have a strong practical emphasis, with regular computer sessions using STATA enabling participants to work through examples.
Target Audience:
The course is aimed at researchers who need to analyse longitudinal survey data, also called panel data or repeated measures data, especially those in the social, economic, educational and medical sciences. Participants should already be familiar with basic statistical theory, including inference, multiple linear regression and logistic regression. Participants may be researchers in the social sciences or may work in government, survey agencies, official statistics or the private sector.
Find out more about Fees, teaching and reading lists
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Highfield campus
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Find out moreSpeaker information
Peter Smith,Professor of Social Statistics in the Social Statistics Division, School of Social Sciences.
Ann Berrington,Reader in Social Statistics in the Social Statistics Division, School of Social Sciences