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Confirmatory Factor Analysis

The Four Models You Meet in Structural Equation Modeling

by guest contributer  5 Comments

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. [Read more…] about The Four Models You Meet in Structural Equation Modeling

Tagged With: CFA, Confirmatory Factor Analysis, EFA, Latent Growth Curve Model, mediation, Path Analysis, SEM, Structural Equation Modeling

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Correlated Errors in Confirmatory Factor Analysis

by Jeff Meyer  3 Comments

Latent constructs, such as liberalism or conservatism, are theoretical and cannot be measured directly.

But we can represent the latent construct by combining a set of questions on a scale, called indicators. We do this via factor analysis.

Often prior research has determined which indicators represent the latent construct. Prudent researchers will run a confirmatory factor analysis (CFA) to ensure the same indicators work in their sample.

[Read more…] about Correlated Errors in Confirmatory Factor Analysis

Tagged With: Confirmatory Factor Analysis, error term, Factor Analysis, latent variable, Model Fit

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Measurement Invariance and Multiple Group Analysis

by Jeff Meyer  2 Comments

Creating a quality scale for a latent construct (a variable that cannot be directly measured with one variable) takes many steps. Structural Equation Modeling is set up well for this task.

One important step in creating scales is making sure the scale measures the latent construct equally well and the same way for different groups of individuals.

[Read more…] about Measurement Invariance and Multiple Group Analysis

Tagged With: Confirmatory Factor Analysis, Exploratory Factor Analysis, Factor Analysis, Structural Equation Modeling

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Why Adding Values on a Scale Can Lead to Measurement Error

by Jeff Meyer  4 Comments

Whenever you use a multi-item scale to measure a construct, a key step is to create a score for each subject in the data set.

This score is an estimate of the value of the latent construct (factor) the scale is measuring for each subject.  In fact, calculating this score is the final step of running a Confirmatory Factor Analysis.

[Read more…] about Why Adding Values on a Scale Can Lead to Measurement Error

Tagged With: Confirmatory Factor Analysis, Exploratory Factor Analysis, Factor Analysis, Structural Equation Modeling

Related Posts

  • Measurement Invariance and Multiple Group Analysis
  • One of the Many Advantages to Running Confirmatory Factor Analysis with a Structural Equation Model
  • First Steps in Structural Equation Modeling: Confirmatory Factor Analysis
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Member Training: A Guide to Latent Variable Models

by Jeff Meyer 

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.

[Read more…] about Member Training: A Guide to Latent Variable Models

Tagged With: Confirmatory Factor Analysis, Growth Mixture Model, latent class analysis, Latent Growth Curve Model, Latent Profile Analysis, Latent Transition Analysis, latent variable, Structural Equation Modeling

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One of the Many Advantages to Running Confirmatory Factor Analysis with a Structural Equation Model

by Jeff Meyer  9 Comments

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.

[Read more…] about One of the Many Advantages to Running Confirmatory Factor Analysis with a Structural Equation Model

Tagged With: CFA, Confirmatory Factor Analysis, Cronbach's alpha, eigenvalue, Factor Analysis, factor loadings, latent construct, Latent Growth Curve Model, latent variable, Model Fit, residuals, SEM, Structural Equation Modeling

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  • The Four Models You Meet in Structural Equation Modeling
  • Three Myths and Truths About Model Fit in Confirmatory Factor Analysis

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