Longitudinal Data Analysis (join a waiting list)

Date:

03/07/2017 - 05/07/2017

Organised by:

NCRM, University of Southampton

Presenter:

Professor Peter Smith, Professor Ann Berrington and Dr Marcel Vieira

Level:

Intermediate (some prior knowledge)

Contact:

Jacqui Thorp
Training and Capacity Building Co-ordinator
NCRM, University of Southampton
Tel: 02380 594069
Email: jmh6@soton.ac.uk

Map:

View in Google Maps  (SO17 1BJ)

Venue:

Building 39, University of Southampton, Highfield, Southampton, Hants

Description:

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 subject-specific models; and methods for handling complex survey designs, weights and non-response.

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
  • Fixed effects models
  • Methods for categorical responses
  • Handling complex survey designs, weights and non-response

The methods will be illustrated and compared using analyses of a variety of socio-economic, attitudinal and health outcomes collected in the British Household Panel Survey and in Understanding Society. The course will have a strong practical emphasis, with regular computer sessions using STATA enabling participants to work through examples.

Learning outcomes:

  • 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.

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.

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. (2012) Multilevel Analysis 2nd Edition. London: Sage.

 

 

Cost:

The fee is:
• £30 per day for UK registered students
• £60 per day for staff at UK academic institutions, RCUK funded researchers, UK public sector staff and staff at UK registered charity organisations
• £220 per day for all other participants.
The course fee includes course materials, lunches and morning and afternoon refreshments. Travel and accommodation are to be arranged and paid for by the participant.
Course places are limited and early registration is strongly recommended.
Full refund will be offered 3 weeks prior to the course taking place. The fees are non-refundable after this date.

Website and registration:

Region:

South West

Keywords:

Longitudinal Data Analysis, Panel data models, Repeated measures , Random effect models , Marginal models

Related publications and presentations:

Longitudinal Data Analysis
Panel data models

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