Message-ID: <483F213B.7080300@ufl.edu>
Date: 2008-05-29T21:33:47Z
From: Ben Bolker
Subject: glm-model evaluation
In-Reply-To: <17993.200.27.188.82.1212094766.squirrel@webmail.udec.cl>
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Ruben Roa Ureta wrote:
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|> Ruben Roa Ureta wrote:
|>
|> | I have traced the rule about 2 as the minimum difference to favour one
|> | model over the other to remark 2, Ch. 4, Sakamoto, Ishiguro and
|> Kitagawa,
|> | 1986, Akaike Information Criterion Statistics. D. Re?dle Publishing Co,
|> | Dordrecht. They use the expression 'significant difference between
|> | models'. However, they do not explain why they think that 2 is the
|> minimum
|> | 'significant' delta AIC. Does anybody know more about a justification
|> for
|> | this threshold?
|> | Rub?n
|>
|> ~ I would really strongly recommend AGAINST trying to justify
|> "significance thresholds" for AIC (B&A 2002 say this too).
|
| Note that I used quotes as in 'significant difference between
| models'. I think the concept of 'significance' as in significance tests
| does not apply to I-T model selection. I only wanted to know about any
| justification for the delta AIC=2 rule.
~ Fair enough. The reason that I (and B&A) react so strongly to the
use of the word "significance" in this context is that it's nearly
impossible to prevent people from misinterpreting it in terms of
classical p-values. It's too bad the word has been tainted so as to make
it practically unusable in this context, but it has. (I have a
similar feeling about calling model weights "probabilities" ...)
~ cheers
~ Ben
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