Longitudinal Data Analysis
Venue: Highfield Campus, University of Southampton, UK
Presenter: Professor Peter Smith, Dr Ann Berrington, Dr Marcel Vieira
Dates of Course: Wednesday 29th June - Friday 1st July 2011
This course has already run. Please check the course listings for a future course.
Summary of Course:
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.
- 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.
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.
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.
Participants on this course must have prior statistical knowledge covering inference, multiple linear and logistic regression for cross-sectional data (for example up to the level of the CASS course ‘Regression Methods').
The course will have a strong practical emphasis, with regular computing sessions, using STATA and real survey data, to enable participants to work through examples. Therefore, prior experience of analysing survey data using a statistical package is required. However, no prior knowledge of STATA will be assumed.
Participants will receive written course notes.
Peter Smith is Professor of Social Statistics in the Social Statistics Division, School of Social Sciences, at the University of Southampton. He is also a member of the Southampton Statistical Sciences Research Institute. He has a BSc in Mathematics and an MSc and PhD in Statistics. His general research interests are in statistical modelling of social and medical data, including longitudinal data analysis. He has extensive experience in teaching short courses, including several courses for CASS on longitudinal data analysis.
Ann Berrington is a Reader in Social Statistics in the Social Statistics Division, School of Social Sciences, at the University of Southampton. She is also a member of the Southampton Statistical Sciences Research Institute. She has a BSc in Human Sciences, an MSc in Medical Demography and a PhD in Social Statistics. Her general research interests are in demography. She has wide-ranging experience in handling and analysing longitudinal survey data. She has also extensive experience in teaching short courses, including several courses for CASS on longitudinal data analysis.
Marcel Vieira is a Senior Lecturer in the Department of Statistics at the Federal University of Juiz de Fora, in Brazil. His current research interests include survey methodology and analysis of longitudinal social science data. He has a BSc in Economics, an MSc in Decision Support Methods and a PhD in Social Statistics. He has taught several CASS courses on longitudinal data analysis.
£30 per day for UK-registered students. £60 per day for staff from UK academic institutions (including research centres), ESRC funded researchers and registered charity organizations. £220 per day for all other participants. The course fee includes course materials, lunches and morning and afternoon tea, but not accommodation and travel which is to be arranged by the participant.
Location and Accommodation:
The course will be held at the 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. Further information on location and accommodation can be obtained from here
The course will begin with coffee and registration at 9.30 a.m. on the first day and finish at 5.00 p.m. on the last day.
For participants who wish to do background reading, the following references may be useful. Please note that although reading is optional, participants who have little statistical background in longitudinal or multilevel modelling are strongly advised to look at some of these references.
- Twisk, J. W. R. (2003) Applied Longitudinal Data Analysis for Epidemiology: A Practical Guide. Cambridge: Cambridge University Press.
- Kreft, I. and de Leeuw, J. (1998) Introducing multilevel modelling. London: Sage.
- Diggle, P. J., Heagerty, P., Liang, K-Y. and Zeger, S. L. (2002) Analysis of Longitudinal Data. Second Edition. Oxford: Oxford University Press.
- Snijders, T. A. B. and Bosker, R. J. (1999) Multilevel Analysis. London: Sage.
Deadlines and Refunds:
Course places are limited and early registration is recommended. Payment must be made when submitting the registration form. A Purchase Order is required for Invoice payments. A copy of the Purchase Order must be emailed, faxed or posted to the CASS Administration Assistant. If you have registered online please ensure that the Purchase Order number is included at the time of registration and that you email, fax or post a copy of the Purchase Order. We are unable to process an Invoice payment without a Purchase Order.
A full refund is available for cancellations made up to one calendar month before the course, but no refunds are available for cancellations after this date. Please note, in case of a cancellation, an administration charge of up to £30 may apply.