Introduction to Structural Equation Modelling and Moderated-Mediation in Mplus

Date:

01/08/2014

Organised by:

University of Ulster

Presenter:

Dr Liam Mahedy (University of Bristol)

Level:

Intermediate (some prior knowledge)

Contact:

Dr Gillian Shorter gw.shorter@ulster.ac.uk

Map:

View in Google Maps  (BT48 7JL)

Venue:

University of Ulster, Magee campus,
Northland Road, Londonderry

Description:

This course introduces structural equation modelling, and provides practical experience in conducting a moderated-mediation model using Mplus. Topics covered include basic components of structural equation modelling, path analysis, direct and indirect effects, interaction effects, and combining moderation and mediation. Conditional indirect effects (moderated mediation) and the mediation of moderated effects (mediated moderation) will both be examined. The activities in this workshop will focus on moderation and mediation, but this will be contextualised within structural equation models.

 

The course is delivered by a combination of lectures and interactive sessions including theoretical concepts and practical examples. Towards the end of the course there will be opportunities to ask questions in relation to analysing your own data. Knowledge of regression is assumed.

Cost:

£120 per day; Reduced to £60 per day for postgraduates, unwaged, or those who work for Charitable organisations (on proof of status). If you book 4 or more days from the list http://science.ulster.ac.uk/bamfordcentre/summer-school/index.php contact flexed@ulster.ac.uk before you book to arrange an extra day training at no additional cost.

Website and registration:

Region:

Northern Ireland

Keywords:

Cross-Sectional Research, Measurement Error, Quantitative Data Handling and Data Analysis, Latent Variable Models, Structural equation models, Moderation , Mediation

Related publications and presentations:

Cross-Sectional Research
Measurement Error
Quantitative Data Handling and Data Analysis
Latent Variable Models
Structural equation models

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