This course aims to provide participants with an introduction to latent variables and structural equation models for both continuous and categorical data and their use in measurement and in modelling complex substantive hypothesis in the social sciences. It provides a balance between methods and applications to enable participants to develop a good understanding of structural equation models and related methods.This course comprises a mixture of lectures on the theory and methodology of latent variable models and structural equation models, followed by practical sessions in which participants will have the opportunity to use STATA and MPlus to run analysis on real data sets.The topics covered will include: an introduction to latent variables, path analysis and structural equation modelling with latent and observed variables, exploratory and confirmatory factor analysis, latent trait analysis, latent class analysis, structural equation models for continuous and categorical observed variables, cross-sectional, longitudinal data and analysis of multi-group (cross-national survey) data.A step-by-step approach will be taken to introduce all topics so that the course will build up from introductory to more advanced material. Participants will receive lecture slides and material for the practical sessions that will include the STATA and MPlus commands.

Course leader
Dr Irini Moustaki

Target group
This course is suitable for postgraduate and academic staff in applied statistics, medicine, and in social and behavioural sciences as well as government employees and people working in marketing, management, public health and banking.

Course aim
This course aims to provide participants with introductions to:- modern statistical methodology for analysing multivariate continuous and categorical data;- the use of latent variables for measuring unobserved constructs such as attitudes, beliefs, health state, etc. through observed indicators.It will also provide participants with experience in:- the use of path models to represent complex relationships among latent and unobserved variables;- modelling relationships among latent constructs and observed covariates and providing the ability to measure direct and indirect (mediation) effects;- modelling cross-sectional data including (as special topics) the treatment of longitudinal data and multi-group data such as cross-national data;- the use of STATA and MPlus software to run real data examples. Participants will have the opportunity to run the analysis and interpret the output.

Credits info
2.5 ECTS The decision to award credits is at the discretion of the student's home institution. Students should always check with their home institution to confirm the number of credits that can be awarded.

Fee info
GBP 935: Student rate - for current university students (including PhD students).Current academic staff and UK charity workers are also eligible for a reduced rate of 1,250. GBP 1575: Standard rate

London School of Economics
Address: Houghton Street
Postal code: WC2A 2AE
City: London
Country: United Kingdom
Website: http://www.lse.ac.uk/study/summerSchools/Methods/home.aspx
E-mail: summer.methods@lse.ac.uk
Phone: +44 (0)20 7955 6422