Structural Equation Modelling
Venue: Highfield Campus, University of Southampton, UK
Presenter: Dr Patrick Sturgis
Dates of Course: Wednesday 4th - Thursday 5th July 2007
This course has already run. Please check the course listings for a future course.
Summary of Course:
This course starts by introducing the ideas of structural equation modelling, before focusing on the use of the models to analyse panel data. Topics will include: cross-lagged panel models, latent curve analysis, multiple group models, growth mixture models and parallel process models.
Note: This course is preceded by a 2 day short course on "Longitudinal Data Analysis". A reduced course fee for both courses will apply.
- To provide an introduction to structural equation modelling.
- To introduce methods for analysing panel data from a structure equation modelling perspective.
This course will include the following topics:
- Introduction to structural equation modelling
- Cross-lagged panel models
- Latent curve analysis
- Methods for adjusting for measurement error
The methods will be illustrated and compared using analyses of attitudes collected in the British Household Panel Survey and the British Election Panel Survey. The course will have a strong practical emphasis, with regular computing sessions enabling participants to work through examples in Mplus for Windows.
The course is aimed at researchers, especially those in the social, economic, educational and medical sciences, who wish to familiarise themselves with structural equation modelling, particularly with the aim of analysing longitudinal survey data, also called panel data or repeated measures data. Participants should already be familiar with basic statistical theory, including inference and multiple linear regression and should have some knowledge of longitudinal data analysis.
Participants on this course must have prior statistical knowledge covering inference and linear regression modelling (up to the level of Survey Data Analysis II) and should have some knowledge of longitudinal data analysis. This course is preceded by a 2 day short course on "Longitudinal Data Analysis" for people with no knowledge of longitudinal data analysis. ( A reduced course fee for both courses will apply.)
The course will have a strong practical emphasis, with regular computing sessions, using Mplus for Windows 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 Mplus will be assumed.
Participants will receive written course notes.
Patrick Sturgis is a Senior Lecturer in Quantitative Sociology in the Department of Sociology at the University of Surrey. He is also an associate member of the Southampton Statistical Sciences Research Institute. He has a BA in Psychology and an MSc and PhD in Social Psychology. One of his research interests is the use of structural equation models in the social sciences.
For UK-based academic researchers the fee is: £40 per day (you must be UK academic staff or an ESRC-funded researcher.)
For UK-registered students the fee is £20 per day
For non-academic researchers or non UK-based academic researchers and students the fee is: £175 per day.
The course fee includes course materials, lunches and morning and afternoon tea, but not accommodation which is to be arranged by the participant.
If a course participant also attends the course on "Longitudinal Data Analysis" (2-3 July 2007) then the course fee for both courses together will reduce to: £590, £140 and £80, respectively.
The course will be held at the Southampton Statistical Sciences Research Institute, Building 39, University of Southampton, Southampton, SO17 1BJ. Further information can be obtained from here.
The course will begin with coffee and registration at 9.30 a.m. on Wednesday, July 4 and finish at 5.30 p.m. on Thursday, July 5.
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 on modelling panel data are strongly advised to look at some of these references.
- Finkel, S. (1995) Causal Analysis with Panel Data. London: Sage.
- Loehlin J. C. (1987) Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis. Hillsdale, H.J.: Lawrence Erlbaum Associates.
- Bollen, K. A. and Curran, P. J. (2006) Latent Variable Models: A Structural Equation Perspective. Hoboken, N.J.: Wiley.
Participants are left to book their own accommodation according to individual needs. Information can be obtained from here.
Deadlines and Refunds:
Course places are limited and early completion of this form is recommended. Payment must be made when submitting the registration form. Refunds for cancellation are as follows. Full refund for cancellation one calendar month before the course, no refunds can be made for cancellations after this date.