Structural Equation Modeling

Moderated mediation, also known as Conditional Process Modeling, is great tool for understanding one type of complex relationship among variables.

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A multiple regression model could be conceptualized using Structural Equation Model path diagrams. That’s the simplest SEM you can create, but its real power lies in expanding on that regression model.  Here I will discuss four types of structural equation models.

Path Analysis

More interesting research questions could be asked and answered using Path Analysis. Path Analysis is a type of structural equation modeling without latent variables. (more…)

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In most regression models, there is one response variable and one or more predictors. From the model’s point of view, it doesn’t matter if those predictors are there to predict, to moderate, to explain, or to control. All that matters is that they’re all Xs, on the right side of the equation.

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What are goodness of fit statistics? Is the definition the same for all types of statistical model? Do we run the same tests for all types of statistic model?

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An extremely useful area of statistics is a set of models that use latent variables: variables whole values we can’t measure directly, but instead have to infer from others. These latent variables can be unknown groups, unknown numerical values, or unknown patterns in trajectories.

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Based on questions I’ve been asked by clients, most analysts prefer using the factor analysis procedures in their general statistical software to run a confirmatory factor analysis.

While this can work in some situations, you’re losing out on some key information you’d get from a structural equation model. This article highlights one of these.

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