Hostname: page-component-5f745c7db-xx4dx Total loading time: 0 Render date: 2025-01-06T07:38:21.122Z Has data issue: true hasContentIssue false

The Relation between Sample and Population Characteristic Vectors

Published online by Cambridge University Press:  01 January 2025

Norman Cliff*
Affiliation:
University of Southern California

Abstract

Data are reported which show the statistical relation between the sample and population characteristic vectors of correlation matrices with squared multiple correlations as communality estimates. Sampling fluctuations were found to relate only to differences in the square roots of characteristic roots and to sample size. A principle for determining the number of factors to rotate and interpret after rotation is suggested.

Type
Original Paper
Copyright
Copyright © 1970 The Psychometric Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

This study was supported by the National Science Foundation, Grant GB 4230. The author wishes to express his appreciation for the use of Western Data Processing Center and the Health Sciences Computing Facility, UCLA. He also thanks Dr. Roger Pennell for extremely valuable assistance in a number of phases of the study.

References

Birkhoff, G. & MacLane, S. A brief survey of modern algebra, Rev. ed., New York: Macmillan, 1953.Google Scholar
Browne, M. W. A comparison of factor analytic techniques. Psychometrika, 1968, 33, 267334.CrossRefGoogle ScholarPubMed
Cliff, N. & Hamburger, C. D. The study of sampling errors in factor analysis by means of artificial experiments. Psychological Bulletin, 1967, 68, 430445.CrossRefGoogle Scholar
Cliff, N. & Pennell, R. The influence of communality, factor strength, and loading size on the sampling characteristics of factor loading. Psychometrika, 1967, 32, 309326.CrossRefGoogle Scholar
Harris, C. W. Some Rao-Guttman relationships. Psychometrika, 1962, 27, 247263.CrossRefGoogle Scholar
Harris, C. W. On factors and factor scores. Psychometrika, 1967, 32, 363379.CrossRefGoogle Scholar
Jöreskog, K. G. Statistical estimation in factor analysis, 1963, Stockholm: Almquist and Wiksell.Google Scholar
Kendall, M. G. & Stuart, A. The advanced theory of statistics. Vol. 2, 1961, London: Charles Griffin.Google Scholar
Kendall, M. G. & Stuart, A. The advanced theory of statistics, 2nd Ed., London: Charles Griffin, 1963.Google Scholar
Pennell, R. J. & Young, F. W. An IBM 7094 program for generating random factor matrices. Behavioral Science, 1967, 12, 165166.Google Scholar
Pennell, R. J. The effect of communality and N on the sampling distributions of factor loadings. Psychometrika, 1968, 33, 423440.CrossRefGoogle Scholar
Tucker, L. R. A method for synthesis of factor studies. Personnel Research Section Report No. 984, 1951, Department of the Army (mimeo.).CrossRefGoogle Scholar