Structural Equation Modelling workshop

Structural equation modelling: Unearthing the data-generating process in agricultural and veterinary science.

A practical workshop on Structural Equation Modelling delivered by Dr Murthy N Mittinty, School of Public Health, The University of Adelaide. 

Structural equation modelling (SEM) is a comprehensive methodology for representing, estimating, and testing hypotheses about correlations and relationships between variables. SEM is already ubiquitous in the social sciences because of its increased flexibility for modelling complex relationships including both measured observations and unobserved (latent) constructs. This workshop will introduce you to this powerful modelling methodology, and how we can build similar models in the domains of the agricultural and veterinary sciences. Participants from School of Agriculture Food and Wine and Animal and Veterinary Sciences will also enjoy post-workshop support with their projects up to two hours of small-group tutorials.

Objectives of the workshop

  1. Conceptualise the research question into a diagrammatic model, and then into the mathematical model which allows you to estimate the parameter of interest.

  2. Learn to create summary variables.

  3. Learn to incorporate the summary variables into the analysis model.

  4. Understand the time order of the presence of variables and study the concept of mediation and moderation.

  5. Understand how the SEM technique allows you to handle the concept of measurement error.

  6. Understand how the SEM technique allows you to handle the concept of missing data.

Intended Audience

Anyone with basic understanding of linear regression analysis. Especially, PhD students, Researchers, and Educators using observational data.

Topics covered

Simultaneous equations, Linear combination of indicators to create summaries, Factor analysis, Definition of Structural Equation Models (SEM), Types of SEM, Benefits of SEM, Drawbacks of SEM, Steps in Structural Equation Modelling, Model specification, Identification, Estimation and evaluation, Parameter testing, Practical issues to consider when implementing SEM, Review questions, Some examples using SPSS and Amos.

Prerequisites

  • Participants are required to bring a laptop with SPSS & Amos installed (available for University of Adelaide staff and students via ADAPT or from ITDS).

Maximum number of attendees: 20. Participants are required to have their own computer.


Outline of the program

Day 1

Time Event
8.30-9.00 Registration
9.10-9.50 Some basic mathematical concepts, simultaneous equations, issues in working with observational data and concept of data reduction.
10.00-10.30 Break
10.35-12.00 Definition of SEM, Types of SEM, Benefits of SEM, Drawbacks of SEM, Steps in Structural Equation Modelling
12.00-1.00 Lunch Break
1.10-2.00 Steps in Structural Equation Modelling
2.10-2.20 Break
2.20-3.10 Practical general
3.10-3.30 Tea break
3.35-4.30 Practical application to your field

 

Day 2

Time Event
9.30-10.30 Model Specification, Identification
10.30-11.00 Break
11.10-12.30 Estimation and Evaluation
12.30-1.30 Lunch Break
1.30-3.00 Practical with SPSS
3.00-3.30 Tea Break
3.30-5.00 Parameter testing and practical issues to consider when implementing SEM

 

Tagged in Biometry Hub, Biometry Training