This paper is from Session 4F: Sensible use of multivariate software

which comes under Topic 4: Statistics education at the post secondary (tertiary) level

Other papers under session 4F ... 4F1: Effect sizes and confidence intervals for multivariate analysis: how... 4F2: A sampling of analyses and software use for cluster randomized trials... 4F3: Applying idiographic research methods: two examples

(Wednesday 14th, 11:00-13:00)

Exploratory factor analysis in Mplus, R and SPSS

Presenter

• Sigbert Klinke (Humboldt University of Berlin, Germany)

Co-authors

• Wolfgang Härdle (Humboldt University of Berlin, Germany)
• Andrija Mihoci (Humboldt University of Berlin, Germany)

Abstract

In teaching, factor analysis and principal component analysis are often used together, although they are quite different methods. We first summarise the similarities and differences between both approaches. From submitted theses it appears that student have difficulties seeing the differences. Although books and online resources mention some of the differences they are incomplete. A view either oriented on the similarities or the differences is reflected in software implementations. We therefore look at the implementations of factor analysis in Mplus, R and SPSS and finish with some conclusions for the teaching of Multivariate Statistics.

Other papers under session 4F ... 4F1: Effect sizes and confidence intervals for multivariate analysis: how... 4F2: A sampling of analyses and software use for cluster randomized trials... 4F3: Applying idiographic research methods: two examples