De grootste kennisbank van het HBO

Inspiratie op jouw vakgebied

Vrij toegankelijk

Terug naar zoekresultatenDeel deze publicatie

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.

OrganisatieHanzehogeschool Groningen
LectoraatStatistical Techniques for Applied Research
Gepubliceerd inPsychometrika. Vol 67(1) Springer Verlag, Vol. 71, Uitgave: 1, Pagina's: 193-199
Datum2006-03-01
TypeArtikel
ISSN0033-3123
DOI10.1007/s11336-000-1142-9
TaalEngels

Op de HBO Kennisbank vind je publicaties van 26 hogescholen

De grootste kennisbank van het HBO

Inspiratie op jouw vakgebied

Vrij toegankelijk