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Convergence of estimates of unique variances in factor analysis, based on the inverse sample covariance matrix

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Convergence of estimates of unique variances in factor analysis, based on the inverse sample covariance matrix

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Samenvatting

If the ratio m/p tends to zero, where m is the number of factors m and p the number of observable variables, then the inverse diagonal element of the inverted observable covariance matrix (σ pjj) -1 tends to the corresponding unique variance ψ jj for almost all of these (Guttman, 1956). If the smallest singular value of the loadings matrix from Common Factor Analysis tends to infinity as p increases, then m/p tends to zero. The same condition is necessary and sufficient for (σ pjj) -1 to tend to ψ jj for all of these. Several related conditions are discussed. © 2006 The Psychometric Society.

OrganisatieHanze
Gepubliceerd inPsychometrika. Vol 67(1) Springer Verlag, Vol. 71, Uitgave: 1, Pagina's: 193-199
Datum2006-03-01
TypeArtikel
DOI10.1007/s11336-000-1142-9
TaalEngels

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