Generalized Procrustes Analysis: a Tool for Exploring Aggregates and Persons
نویسندگان
چکیده
Gower (1975) introduced Generalized Procrustes Analysis (GPA) as a multivariate statistical technique for analyzing three-dimensional data matrices. The current paper presents a non-technical introduction to the logic underlying GPA and then presents a completely worked example using genuine data. Specifically, self and peer ratings obtained from students attending a Summer Science Academy are analyzed and discussed. It is shown that GPA offers a powerful set of tools for exploring data at both the aggregate and individual level. A number of issues regarding the current analysis methods are also discussed. INTRODUCTION Imagine a female student who rates herself and nine other people whom she knows personally on 30 adjective trait terms (e.g., friendly, outgoing, agreeable) using a 5-point Likert-type scale. A personality psychologist subsequently records her responses in a 30 x 10 2-dimensional matrix: The psychologist next recruits more people to participate in the study, obtaining 49 additional 30 x 10 matrices: Person #1
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