StatsTips

Confirmatory Factor Analysis (CFA) is a statistical technique used to test and confirm the factor structure of a set of observed variables based on a hypothesized model. Unlike Exploratory Factor Analysis (EFA), which aims to explore and uncover the underlying structure of a dataset, CFA is used to evaluate whether a pre-specified factor model fits the data well. Here’s how confirmatory factor analysis works: Hypothesized Model Specification: Before conducting CFA, researchers specify a theoretical model that represents the relationships among…

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Exploratory Factor Analysis (EFA) is a statistical technique used to uncover the underlying structure or patterns in a dataset, particularly when dealing with a large number of variables. It aims to identify the underlying factors that explain the correlations among observed variables. Here’s how exploratory factor analysis works: Data Preparation: EFA typically begins with a dataset containing multiple observed variables (e.g., survey items, test scores). Factor Extraction: The goal of factor extraction is to identify a smaller number of underlying…

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