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The Influence of Communality and N on the Sampling Distributions of Factor Loadings

Published online by Cambridge University Press:  01 January 2025

Roger Pennell
Roger Pennell*
Affiliation:
University of Southern California
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Abstract

The effects of N and communality on the variability of zero and nonzero factor loadings were assessed using a Monte Carlo approach. It was found that increasing N or communality resulted in decreased sampling error of individual factor loadings, but for zero loadings N was found to have the greatest influence. It was also found that distributions of factor loadings become relatively elongated as communality increases.

Keywords

Public PolicyFactor LoadingGreat InfluenceStatistical TheorySampling Error

Information

Type
Original Paper
Information
Psychometrika , Volume 33 , Issue 4 , December 1968 , pp. 423 - 439
Copyright
Copyright © 1968 Psychometric Society

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Footnotes

*

This article is based upon a dissertation submitted to the Graduate School of the University of Southern California in partial fulfillment of the requirements for the Ph.D. degree. The research was supported in part by NSF Grant GB4230. Computing assistance was obtained from the Western Data Processing Center, Health & Sciences Computing Facility and the Computing Sciences Laboratory. The author wishes to thank Drs. Norman Cliff and Forrest Young for valuable suggestions and a reading of the manuscript.

†

Presently at the Educational Testing Service.

References

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