This paper is addressed to the classical problem of
estimating factor loadings under the condition that the sum
of squares of off-diagonal residuals be minimized.
Communalities consistent with this criterion are produced
as a by-product. The experimental work included several
alternative algorithms before a highly efficient method was
developed. The final procedure is illustrated with a
numerical example. Some relationships of minres to
principal-factor analysis and maximum-likelihood factor
estimates are discussed, and several unresolved problems
are pointed out.
%0 Journal Article
%1 harman.jones:factor
%A Harman, Harry H.
%A Jones, Wayne H.
%D 1966
%J Psychometrika
%K Assessment, Behavorial Education, Evaluation, Law Methods, Policy, Psychometrics, Public Science, Social Statistical Statistics Testing Theory and for statistic
%N 3
%P 351--368
%R 10.1007/BF02289468
%T Factor analysis by minimizing residuals (minres)
%U http://link.springer.com/article/10.1007/BF02289468
%V 31
%X This paper is addressed to the classical problem of
estimating factor loadings under the condition that the sum
of squares of off-diagonal residuals be minimized.
Communalities consistent with this criterion are produced
as a by-product. The experimental work included several
alternative algorithms before a highly efficient method was
developed. The final procedure is illustrated with a
numerical example. Some relationships of minres to
principal-factor analysis and maximum-likelihood factor
estimates are discussed, and several unresolved problems
are pointed out.
@article{harman.jones:factor,
abstract = {This paper is addressed to the classical problem of
estimating factor loadings under the condition that the sum
of squares of off-diagonal residuals be minimized.
Communalities consistent with this criterion are produced
as a by-product. The experimental work included several
alternative algorithms before a highly efficient method was
developed. The final procedure is illustrated with a
numerical example. Some relationships of minres to
principal-factor analysis and maximum-likelihood factor
estimates are discussed, and several unresolved problems
are pointed out.},
added-at = {2017-03-30T21:37:25.000+0200},
author = {Harman, Harry H. and Jones, Wayne H.},
biburl = {https://www.bibsonomy.org/bibtex/2e8341fe834bcadce3fe3a913e78c1376/sveng},
doi = {10.1007/BF02289468},
interhash = {f818911f6d92a01cdcf41cb65b6d273a},
intrahash = {e8341fe834bcadce3fe3a913e78c1376},
issn = {0033-3123, 1860-0980},
journal = {Psychometrika},
keywords = {Assessment, Behavorial Education, Evaluation, Law Methods, Policy, Psychometrics, Public Science, Social Statistical Statistics Testing Theory and for statistic},
language = {en},
number = 3,
pages = {351--368},
timestamp = {2017-04-01T10:44:00.000+0200},
title = {Factor analysis by minimizing residuals (minres)},
url = {http://link.springer.com/article/10.1007/BF02289468},
urldate = {2013-06-29},
volume = 31,
year = 1966
}