This tutorial looks at the popular psychometric procedures of factor analysis, principal component analysis (PCA) and reliability analysis. Factor analysis is a multivariate technique for identifying whether the correlations between a set of observed variables stem from their relationship to one or more latent variables in the data, each of which takes the form of a linear model. In comparison PCA is a multivariate technique for identifying the linear components of a set of variables. Both are methods for reducing down large numbers of variables into smaller clusters (factors or components).


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Factor Analysis/PCA Using IBM SPSS Statistics

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