Interpreting the Likelihood Ratio Statistic in Factor Models When Sample Size is Small
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| dc.contributor.author | Geweke John | en_US |
| dc.contributor.author | Singleton K. | en_US |
| dc.contributor.editor | en_US | |
| dc.date.accessioned | 2011-02-07T06:17:46Z | |
| dc.date.available | 2011-02-07T06:17:46Z | |
| dc.date.issued | 1980 | en_US |
| dc.identifier | 2008008405 | en_US |
| dc.identifier.citation | Geweke John and Singleton K. 1980, 'Interpreting the Likelihood Ratio Statistic in Factor Models When Sample Size is Small', American Statistical Association, vol. 75, no. 369, pp. 133-137. | en_US |
| dc.identifier.issn | 0162-1459 | en_US |
| dc.identifier.other | C1 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10453/12981 | |
| dc.description.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. | en_US |
| dc.language | en_US | |
| dc.publisher | American Statistical Association | en_US |
| dc.relation.isbasedon | NA | en_US |
| dc.title | Interpreting the Likelihood Ratio Statistic in Factor Models When Sample Size is Small | en_US |
| dc.parent | Journal of the American Statistical Association | en_US |
| dc.journal.volume | 75 | en_US |
| dc.journal.number | 369 | en_US |
| dc.publocation | USA | en_US |
| dc.identifier.startpage | 133 | en_US |
| dc.identifier.endpage | 137 | en_US |
| dc.cauo.name | BUS.Faculty of Business | en_US |
| dc.conference | Verified OK | en_US |
| dc.for | 010405 | en_US |
| dc.personcode | 101228;0000053819 | en_US |
| dc.percentage | 000100 | en_US |
| dc.classification.name | Statistical Theory | en_US |
| dc.classification.type | FOR-08 | en_US |
| dc.edition | en_US | |
| dc.custom | en_US | |
| dc.date.activity | en_US | |
| dc.location.activity | en_US | |
| dc.description.keywords | Asymptotic distribution; Exploratory factor analysis; Maximum likelihood estimation; Monte Carlo experiments; Finite samples | en_US |
| dc.staffid | University of Minnesota | en_US |
