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A comparison between two analytic rotational solutions where the number of factors is indeterminate

1964; Wiley; Volume: 9; Issue: 1 Linguagem: Inglês

10.1002/bs.3830090112

1099-1743

Harvey F. Dingman, Curtis R. Miller, Richard K. Eyman,

Sensory Analysis and Statistical Methods

Behavioral ScienceVolume 9, Issue 1 p. 76-80 Article A comparison between two analytic rotational solutions where the number of factors is indeterminate Harvey F. Dingman, Harvey F. Dingman Pacific State Hospital, Pomona, CaliforniaSearch for more papers by this authorCurtis R. Miller, Curtis R. Miller Pacific State Hospital, Pomona, CaliforniaSearch for more papers by this authorRichard K. Eyman, Richard K. Eyman Pacific State Hospital, Pomona, CaliforniaSearch for more papers by this author Harvey F. Dingman, Harvey F. Dingman Pacific State Hospital, Pomona, CaliforniaSearch for more papers by this authorCurtis R. Miller, Curtis R. Miller Pacific State Hospital, Pomona, CaliforniaSearch for more papers by this authorRichard K. Eyman, Richard K. Eyman Pacific State Hospital, Pomona, CaliforniaSearch for more papers by this author First published: 1964 https://doi.org/10.1002/bs.3830090112Citations: 9AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL References Carroll, J. B. Biquartimin criterion for rotation to oblique simple structure in factor analysis. Science, 1957, 126, 1114– 1115. Carroll, J. B. The nature of the data, or how to choose a correlation coefficient. Psychometrika, 1961, 26, 347– 372. Cattell, R. B. Factor analysis. New York: Harper, 1952. Dingman, H. F. The dependence of factorial analysis upon the correlation statistic. Unpublished doctoral dissertation, University of Southern California at Los Angeles, 1955. Dingman, H. F. The relation between coefficients of correlation and difficulty factors. Brit. J. stat. Psychol., 1958, 11, 14– 17. Eyman, R. K., Dingman, H. F., & Meyers, C. E. Comparison of some computer techniques for factor analytic rotation. Ed. Psych. Measmt., 1962, 22, 201– 214. Gibson, W. A. Nonlinear factors in two dimensions. Psychometrika, 1960, 25, 381– 392. Guttman, L. Simple proofs of relations between the communality problem and multiple correlation. Psychometrika, 1957, 22, 147– 157. Guttman, L. To what extent can communalities reduce rank? Psychometrika, 1958, 63, 297– 308. Kaiser, H. F. Comments on communalities and the number of factors. Paper read at Conference on the Communality Problem in Factor Analysis, Washington University, St. Louis, May 14, 1960. Lawley, D. N. Tests of significance for the latent roots of covariance and correlation matrices. Biometrika, 1956, 43, 128– 136. Navarro, S. O. Centroid method. AM 557, Southwest Research Institute, San Antonio, Texas, 1957. Rao, C. R. Some statistical methods for comparison of growth curves. Biometrics, 1955, 14. Thurstone, L. L. Multiple-factor analysis. Chiago: Univ. of Chicago Press, 1947. University of California at Los Angeles, School of Medieine, Department of Preventive Medicine and Public Health, Division of Biostatistics. BIMD Computer Programs Manual. Los Angeles: Univ. of California Press, 1961. Zimmerman, W. S. A revised orthogonal rotational solution for Thurstone's original primary mental abilities test battery. Psychometrika, 1953, 18, 77– 93. Citing Literature Volume9, Issue11964Pages 76-80 ReferencesRelatedInformation