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Interpreting the Likelihood Ratio Statistic in Factor Models When Sample Size is Small

Interpreting the Likelihood Ratio Statistic in Factor Models When Sample Size is Small Abstract The use of the likelihood ratio statistic in testing the goodness of fit of the exploratory factor model has no formal justification when, as is often the case in practice, the usual regularity conditions are not met. In a Monte Carlo experiment it is found that the asymptotic theory seems to be appropriate when the regularity conditions obtain and sample size is at least 30. When the regularity conditions are not satisfied, the asymptotic theory seems to be misleading in all sample sizes considered. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the American Statistical Association Taylor & Francis

Interpreting the Likelihood Ratio Statistic in Factor Models When Sample Size is Small

Interpreting the Likelihood Ratio Statistic in Factor Models When Sample Size is Small

Journal of the American Statistical Association , Volume 75 (369): 5 – Mar 1, 1980

Abstract

Abstract The use of the likelihood ratio statistic in testing the goodness of fit of the exploratory factor model has no formal justification when, as is often the case in practice, the usual regularity conditions are not met. In a Monte Carlo experiment it is found that the asymptotic theory seems to be appropriate when the regularity conditions obtain and sample size is at least 30. When the regularity conditions are not satisfied, the asymptotic theory seems to be misleading in all sample sizes considered.

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References (7)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1537-274X
eISSN
0162-1459
DOI
10.1080/01621459.1980.10477442
Publisher site
See Article on Publisher Site

Abstract

Abstract The use of the likelihood ratio statistic in testing the goodness of fit of the exploratory factor model has no formal justification when, as is often the case in practice, the usual regularity conditions are not met. In a Monte Carlo experiment it is found that the asymptotic theory seems to be appropriate when the regularity conditions obtain and sample size is at least 30. When the regularity conditions are not satisfied, the asymptotic theory seems to be misleading in all sample sizes considered.

Journal

Journal of the American Statistical AssociationTaylor & Francis

Published: Mar 1, 1980

Keywords: Asymptotic distribution; Exploratory factor analysis; Maximum likelihood estimation; Monte Carlo experiments; Finite samples

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