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EFA

Confirmatory Factor Analysis: How To Measure Something We Cannot Observe or Measure Directly

by guest contributer Leave a Comment

by Christos Giannoulis, PhD

Many times in science we are intrigued to measure an underlying characteristic that cannot be observed or measured directly. This measure is hypothesized to exist to explain variables, such as behavior, that can be observed.

The measurable variables are called manifest variables. The unmeasurable are called latent variables.

Latent variables are often called factors, especially in the context of factor analysis.

[Read more…] about Confirmatory Factor Analysis: How To Measure Something We Cannot Observe or Measure Directly

Tagged With: CFA, Confirmatory Factor Analysis, EFA, Error, Exploratory Factor Analysis, latent variable, manifest variable, measurement, random error, True Score

Related Posts

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  • First Steps in Structural Equation Modeling: Confirmatory Factor Analysis
  • Measurement Invariance and Multiple Group Analysis
  • Why Adding Values on a Scale Can Lead to Measurement Error

Four Common Misconceptions in Exploratory Factor Analysis

by guest contributer Leave a Comment

by Christos Giannoulis, PhD

Today, I would like to briefly describe four misconceptions that I feel are commonly perceived by novice researchers in Exploratory Factor Analysis:

Misconception 1: The choice between component and common factor extraction procedures is not so important.

In Principal Component Analysis, a set of variables is transformed into a smaller set of linear composites known as components. This method of analysis is essentially a method for data reduction.

[Read more…] about Four Common Misconceptions in Exploratory Factor Analysis

Tagged With: common factor analysis, communality, EFA, eigenvalue, Exploratory Factor Analysis, oblique rotation, orthogonal rotation, PCA, principal axis factor analysis, principal component analysis, rotation, sample size, simple structure

Related Posts

  • In Factor Analysis, How Do We Decide Whether to Have Rotated or Unrotated Factors?
  • Can You Use Principal Component Analysis with a Training Set Test Set Model?
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  • How To Calculate an Index Score from a Factor Analysis

The Four Models You Meet in Structural Equation Modeling

by guest contributer 5 Comments

By Manolo Romero Escobar

On a previous post (Why do I need to have knowledge of multiple regression to understand SEM?) we showed how 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 ways to do that.

Path Analysis

More interesting research questions could be asked and answered using Path Analysis. Path Analysis is the application 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

Related Posts

  • One of the Many Advantages to Running Confirmatory Factor Analysis with a Structural Equation Model
  • First Steps in Structural Equation Modeling: Confirmatory Factor Analysis
  • Member Training: Reporting Structural Equation Modeling Results
  • Three Myths and Truths About Model Fit in Confirmatory Factor Analysis

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