Exploratory Factor Analysis «Free Access»

: Scores representing the amount of variance accounted for by each underlying factor. Factors with eigenvalues greater than 1.0 are often considered important.

Exploratory Factor Analysis (EFA) is a multivariate statistical method used to uncover the underlying structure—or latent constructs—that explain correlation patterns between a set of observed variables. It is primarily used when researchers have no prior hypothesis about the data's nature and want to identify which variables group together to form common themes. Exploratory Factor Analysis

: The proportion of variance in each observed variable that is explained by the extracted common factors. The EFA Step-by-Step Procedure Exploratory Factor Analysis EFA in SPSS : Scores representing the amount of variance accounted