Structural Equation Models have a number of advantages over simple regression models including the modelling of pathways (eg. variable A predicts B, which predicts C, which predicts D) and the inclusion of latent variables (variables which are not measured directly during data collection, but whose values are determined during the statistical modelling).

In this workshop we will cover:

• Foundations of SEM (Including correlation, regression, latent and measured variables)

• The stages of fitting an SEM model (specification, identification, estimation, testing, and modification)

• Assessing model fit

• Fitting a number of models using SEM including

  • Regression models

  • Path models

  • Confirmatory factor analysis

  • Multilevel models

  • Latent growth models

• Advice on reporting SEM results

This workshop consists of 4 x 1.5 hour sessions in PowerPoint, and 4 x 1.5 hour practical sessions in SPSS and AMOS

This workshop is intended for non-statisticians and statisticians new to the field of structural equation modelling. A basic knowledge of correlation and linear regression is assumed.

These workshops are designed for a broad range of participants, researchers from various application fields who only spend a small portion of their time doing statistics (but researchers who when they do statistics want to be doing statistics well). Communicating complex statistical ideas to a non-statistical audience requires significant skill. Equations for example are vital for statisticians who want to describe statistical models accurately but succinctly, however these equations can be a stumbling block for a larger audience who are not used to working with complex equations. We think one sign of a good statistician is that they know the pictures that go on behind the equations, and in our workshops we focus on the pictures rather than the equations.

Working with this broad audience we teach complex statistical theory (we find it heart-breaking when excellent research studies are undone by a poor understanding of underlying statistical theory), but we teach this theory using a number of practical real-world examples. We are also a strong believer in the use of humour in a training context, where humour means that participants are more likely to relax in a training context, to engage with the training content and the presenter, and are more comfortable to ask the questions that they really want to ask about the content as a result.

Each workshop will be capped at 20 participants.