Skip to main content
NZSSN Social Statistics Network logo
  • Home
  • About
  • Courses
  • People
  • Links
  • Contact
Home » Courses

Introduction to Structural Equation Modelling Using AMOS™

Dates: 
February 13, 2012 - February 17, 2012
Instructor: 
Assoc. Prof. Everarda Cunningham

The course is designed as an introductory, applied course in the use of Structural Equation Modelling (SEM) using the Amos18 program. SEM is used widely by researchers to find and test complex relationships amongst observed (measured) variables and latent (unobserved) variables and amongst the latent variables themselves.
 
SEM subsumes other analytical techniques such as regression, path analysis, factor analysis, and canonical correlation. Because of its user-friendly graphics interface, Amos is an ideal way to learn the principles of model analyses using SEM.
 

Prerequisites: 

An understanding of multiple regression is essential and knowledge of exploratory factor analysis is highly desirable. It is also expected that participants have previous experience with a statistical data analysis package such as SPSS. However, the course assumes that participants have little or no prior knowledge of SEM.
 

Learning Objectives: 

The course is divided into three parts and follows the historical development of SEM.
 
Part I is concerned with directly observed variables. Topics include regression and path analysis, and model testing of causal models with observed variables.
 
Part II of the course introduces latent (unobserved) variables. Topics include confirmatory factor analysis (CFA), model comparisons, model equivalence and higher-order CFA, formative versus reflective indicators, and invariance testing via multi-group analyses.
 
Part III combines the ideas covered in the first two parts by introducing full SEM models as path models amongst latent variables. Topics include single indicator latent variable models, and mediating, potentially moderating (interaction) and alternate models in SEM. Throughout the course issues related to fitting structural models are addressed. These include model specification, identification and estimation, assessing model fit (goodness-of-fit criteria), and dealing with problem data including missing data, small samples, ordinal and/or dichotomous variables, non-normal data, non-positive definite matrices and inadmissible models.
 
Course participants will be provided with instruction and practical experience in the use of Amos to estimate parameters implied by various types of models. On the final day of the course, participants will be given the opportunity to ask questions about their own research and receive feedback on their models. Participants wishing to bring their own data should bring an SPSS (*.sav) file or Excel (*.xlsx) file.
 

Course Text: 

Cunningham, E. (2009). A practical guide to structural equation modelling using Amos™. Melbourne: Statsline.
 
This text of the instructor’s course notes will be distributed to all course participants.
 
While no pre-reading in SEM is required and all necessary materials will be provided for the course, interested participants may wish to consult the following reference as preliminary reading:
 

References: 

Kline, R. B. (2005). Principles and Practice of Structural Equation Modeling (2nd Ed.). NY: The Guilford Press.

 

Related Courses/Experience: 

Participants with a good understanding of this course may progress to Advanced Structural Equation Models using Mplus.

2012 Summer Programme
Second week in progress
Thanks to all attendees!

Advanced Qualitative Data Analysis using NVivo 9 (3 days) (CANCELLED)
Advanced Structural Equation Models using Mplus
Applied Computer-assisted Qualitative Data Analysis using NVivo
Case Study Research
Data Analysis using Stata
Fundamentals of SPSS (CANCELLED)
Intermediate Statistics (CANCELLED)
Introduction to Program Evaluation
Introduction to Social Network Research and Analysis (CANCELLED)
Introduction to Statistics
Introduction to Structural Equation Modelling Using AMOS™
Introduction to Survey Design
Introductory Bayesian Statistics (CANCELLED)
Longitudinal Data Analysis
Mathematics for Statistics (3 days) (CANCELLED)
Q Methodology (2 days)
Qualitative Research Techniques
Using Mixed Methods in Research and Program Evaluation

Selected course(s)

You have no selected course(s).

0 Items $0.00
Website hosted by:
Ngā Pae o te Māramatanga
© 2010 New Zealand Social Statistics Network | Powered by Drupal | E-commerce by Reign | Design by AOC