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.
Keywords
StatisticSample size determinationGoodness of fitMathematicsStatisticsMonte Carlo methodAsymptotic analysisLikelihood-ratio testSample (material)Likelihood principleEconometricsMaximum likelihoodLikelihood functionQuasi-maximum likelihoodPhysics
Affiliated Institutions
Related Publications
Can test statistics in covariance structure analysis be trusted?
Covariance structure analysis uses chi 2 goodness-of-fit test statistics whose adequacy is not known. Scientific conclusions based on models may be distorted when researchers vi...
The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis.
Monte Carlo computer simulations were used to investigate the performance of three X 2 test statistics in confirmatory factor analysis (CFA). Normal theory maximum likelihood )~...
Goodness-of-Fit Testing for Latent Class Models
Latent class models with sparse contingency tables can present problems for model comparison and selection, because under these conditions the distributions of goodness-of-fit i...
Nonconcave penalized likelihood with a diverging number of parameters
A class of variable selection procedures for parametric models via nonconcave penalized likelihood was proposed by Fan and Li to simultaneously estimate parameters and select im...
Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification.
This study evaluated the sensitivity of maximum likelihood (ML)-, generalized least squares (GLS)-, and asymptotic distribution-free (ADF)-based fit indices to model misspecific...
Publication Info
- Year
- 1980
- Type
- article
- Volume
- 75
- Issue
- 369
- Pages
- 133-137
- Citations
- 198
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
198
OpenAlex
Cite This
John Geweke,
Kenneth J. Singleton
(1980).
Interpreting the Likelihood Ratio Statistic in Factor Models When Sample Size is Small.
Journal of the American Statistical Association
, 75
(369)
, 133-137.
https://doi.org/10.1080/01621459.1980.10477442
Identifiers
- DOI
- 10.1080/01621459.1980.10477442