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EFFICIENCY OF ESTIMATION WHEN THERE IS ONLY ONE COMMON FACTOR
Author(s) -
Lord Frederic M.,
Wingersky Marilyn S.
Publication year - 1971
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1971.tb00464.x
Subject(s) - estimator , mathematics , covariance , statistics , factor (programming language) , set (abstract data type) , estimation , factor analysis , econometrics , computer science , management , economics , programming language
Explicit formulae are derived for the asymptotic sampling variances and covariances of the maximum‐likelihood estimators for factor‐analysis parameters in the special case where there is just one common factor. The effect of the number of variables on these variances and covariances is indicated. A formula is given showing to what extent the usual covariance between two of a set of variables can be estimated more efficiently when there is known to be just one common factor.