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AIC and Large Samples
I. A. Kieseppä
Philosophy of Science
Vol. 70, No. 5, Proceedings of the 2002 Biennial Meeting of The Philosophy of Science AssociationPart I: Contributed PapersEdited by Sandra D. Mitchell (December 2003), pp. 1265-1276
Stable URL: http://www.jstor.org/stable/10.1086/377406
Page Count: 12
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I discuss the behavior of the Akaike Information Criterion in the limit when the sample size grows. I show the falsity of the claim made recently by Stanley Mulaik in Philosophy of Science that AIC would not distinguish between saturated and other correct factor analytic models in this limit. I explain the meaning and demonstrate the validity of the familiar, more moderate criticism that AIC is not a consistent estimator of the number of parameters of the smallest correct model. I also give a short explanation why this feature of AIC is compatible with the motives for using it.
Copyright 2003 by the Philosophy of Science Association. All rights reserved.