Convergence of estimates of unique variances in factor analysis, based on the inverse sample covariance matrix
Convergence of estimates of unique variances in factor analysis, based on the inverse sample covariance matrix
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.
Organisatie | Hanze |
Gepubliceerd in | Psychometrika. Vol 67(1) Springer Verlag, Vol. 71, Uitgave: 1, Pagina's: 193-199 |
Datum | 2006-03-01 |
Type | Artikel |
DOI | 10.1007/s11336-000-1142-9 |
Taal | Engels |