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).
- PDF Handout on questionnaire design
- PDF Handout on factor analysis/PCA using SPSS
- PDF Handout on reliability using IBM SPSS Statistics
- Data Files