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AIC and Large Samples

Published online by Cambridge University Press:  01 January 2022

Abstract

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.

Type
Confirmation and Statistical Inference
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

I would like to express my gratitude to Stanley Mulaik and Malcolm Forster for our discussions on the topics addressed in this paper.

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