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Structural Equation Modelling (SEM) using AMOS Software

This one-day introductory course will explain what is SEM? The terminology of SEM explained. When to use SEM. What are the appropriate research areas best suited for SEM. Data types and sample size appropriate for SEM.  How to use SEM through SPSS AMOS software. How to draw  complex models of measured variables, latent construct with measured items, and moderators and mediators. How to validate a Model fitness and interpret the Confirmatory Factor Analysis (CFA) of the Data Model against the Theoretical Model.

Aimed at

The target audience for this course are – academic researchers, research assistants, PhD students, Post-Doctoral Researchers, who want to have a clear understanding of Structural Equation Modeling using AMOS graphics.

Pre-requisites

A knowledge of multiple linear regression and factor analysis are useful.

Key learning outcomes

  • What is Structural Equation Modeling (SEM)?
  • Benefits of SEM over Ordinary Least Squares Regression
  • Understanding the Terminology of SEM
  • Scope of Usage of SEM
  • Examples of Theoretical Models to apply Confirmatory Factor Analysis on
  • Model Identification
  • Reliability Testing of Latent Variable Items
  • Evaluating Model Fitness
  • Assessment of Normality of the Data
  • Sample Size and Assumptions
  • Applying Confirmatory Factor Analysis for Measured Variables and Latent Construct
  • Specify and Draw the Theoretical Model using AMOS Graphics
  • Import the Associated Data to carry out CFA
  • Choose your optional Outputs and Calculate Estimates and Path Analysis
  • Check Model Identification and Modify the Model to Obtain Fitness
  • Interpret the CFA of the Data Model against the Theoretical Model

Presented by

Elizabeth Wiredu, Elizabeth Training Limited, www.elizabethtraining.co.uk

Specific skills focused on in this session

Research and information literacy, critical thinking skills

Health and Safety and general notice

Participants will be viewing presentations projected onto a SMART Board screen. Participants will be required to use a desktop PC or laptop during the workshop.

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This workshop is provided by

Brunel Graduate School Logo

Email address graduateschool@brunel.ac.uk Telephone number 01895 265935