Multilevel Structural Equation Modelling with Mplus (3 days)

Date:

04/09/2015 - 06/09/2015

Organised by:

The Psychometrics Centre, University of Cambridge

Presenter:

Dr Arielle Bonneville-Roussy
Dr Gabriela Roman

Level:

Intermediate (some prior knowledge)

Contact:

Arielle -arielle.bonnevilleroussy@gmail.com
Gabriela - gdp27@cam.ac.uk

Map:

View in Google Maps  (CB2 3RQ)

Venue:

Seminar Room (1st floor)
University of Cambridge
Free School Lane
Cambridge, UK

Description:

The aim of the course is to provide an introduction to Multilevel SEM  using Mplus

This course can be taken in combination with the Structural Equation Modelling and the Longitudinal data Analysis with Mplus courses.

In a nutshell, the topics covered are: multilevel regression, multilevel moderation and mediation, multilevel EFA and CFA and multi-level SEM.  No prior knowledge of these topics or is assumed. However, it is assumed that you have acquired knowledge-base of these topics using single-level regression by your own or by having attended the 3-day course on Structural Equation Modelling with Mplus given by The Psychometrics Centre (see website). If you are not familiar with Mplus or with SEM, you need to take the SEM with Mplus course prior to this one order to cope with the remainder of the course. At the end of the course, the participants should have an understanding of the topics covered and be able to conduct multilevel structural equation models in Mplus.

Cost:

Any 2 days £320
Any 3 days £420
Any 5 days £600
8 says £800

Website and registration:

Region:

East of England

Keywords:

Cross-Sectional Research, Longitudinal Research , Experimental Research , Quantitative Data Handling and Data Analysis, Statistical Theory and Methods of Inference, Regression Methods, Hierarchical models, Mixed models, Random effects, Multilevel Latent Variable,Multilevel Factor analysis,Multilevel Confirmatory factor analysis,Multilevel Structural equation models, Mplus

Related publications and presentations:

Cross-Sectional Research
Longitudinal Research
Experimental Research
Quantitative Data Handling and Data Analysis
Statistical Theory and Methods of Inference
Regression Methods
Hierarchical models
Mixed models
Random effects

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