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Separation of Data as a Principle in Factor Analysis

Published online by Cambridge University Press:  01 January 2025

Chester W. Harris*
Affiliation:
University of Wisconsin

Abstract

Two systems of factor analysis—factoring correlations with units in the diagonal cells and factoring correlations with communalities in the diagonal cells—are considered in relation to the commonly used statistical procedure of separating a set of data (scores) into two or more parts. It is shown that both systems of factor analysis imply the separation of the observed data into two orthogonal parts. The matrices used to achieve the separation differ for the two systems of factor analysis.

Information

Type
Original Paper
Copyright
Copyright © 1955 The Psychometric Society

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