Structural Equation Modelling
Date: 21st - 22nd March 2012
Duration: 2 days
Delivered by: Dr. Mick Green and Karen Dunn
Registration deadline has passed.
Please contact firstname.lastname@example.org for more information about this course.
- External from industry/commerce - £440
- External from an academic institution/public sector/charity - £120
- External postgraduate student - £60
- Lancaster University staff - £120
- Lancaster University postgraduate student - £60
- Members of Mathematics and Statistics at Lancaster University - £ 0
This course will introduce participants to latent variables (variables which are not directly measured themselves) and to the use of factor analysis in investigating relationships between latent variables and observed, or measured, variables. These techniques will then be extended into the wider area of structural equation modelling, where complex models involving several latent variables will be introduced.
The course is aimed at researchers and research students who have experience of statistical modelling (up to linear regression) and hypothesis testing, who wish to develop techniques to analyse more complex data involving latent variables. The aim of the course is to provide a background of theory with opportunities to apply the techniques in practice, and each session will consist of a lecture/ demonstration and a practical. The software packages used will be SPSS and AMOS, and while participants will be expected to be familiar with SPSS, no knowledge of the structural equation modelling package AMOS will be assumed.
- introduction to latent variables and measurement error
- exploratory and confirmatory factor analysis
- measurement models
- structural equation modelling
- familiar with latent variables and factor models
- able to investigate data using factor analysis
- able to confirm hypotheses and develop structural equation models
- able to apply theoretical concepts
- able to identify and solve problems
- able to analyse data using appropriate techniques and interpret statistical output