Writing about Structural Equation Modelling

Abstract

Chapter 10 addressed confirmatory factor analysis (CFA) which is a technique using structural equation modelling (SEM). Studies using SEM are becoming more common in applied linguistics as it is possible to test complex models using these techniques, also the software available to conduct SEM is becoming more user friendly. SEM is also known as causal modelling, although the notion of causality needs to be addressed very cautiously as a SEM model cannot prove cause and effect. It tests a model that is deemed acceptable, but this does not represent the only possible model. SEM is based on correlation and regression and uses these techniques to test theories. A visual hypothesised model is produced that reflects relationships between independent variables (IVs) and dependent variables (DVs). The model is then tested for ‘fit’ using statistical analyses. This chapter is about the most important requirements for writing about SEM. The chapter covers the following topics: Technical information Measurement and structural models Stages in SEM Fit indices and model fit for SEM models Examples Hypothesised model Steps in SEM Fit indices Model specification Model modification Model fit Path diagrams KeywordsStandardize Root Mean Square ResidMotivation OrientationStructural Equation Modelling AnalysisStructural Equation Modelling ModelStructural Equation Modelling TechniqueThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.