On 02/08/12 18:02, Bert Gunter wrote:
Well, geez! Without trying to upstage SImon, why not google it yourself?!
http://en.wikipedia.org/wiki/Akaike_information_criterion
-- one or two slightly surprising statements in there though :-)
I quite like the coverage in Davison (2003) "Statistical Models" Section
4.7. Burnham and Anderson (2002) "Model Selection and Multi Model
inference: a practical information theoretic approach", Springer, is a
longer treatment.
best,
Simon
(seemed pretty clear to me...)
-- Bert
On Thu, Aug 2, 2012 at 9:54 AM, Will Shadish <wshad...@ucmerced.edu> wrote:
Simon, could you clarify this paragraph. We are submitting to a psychology
journal and I am certain they will be asking us about why it is still ok to
use AIC for non-nested models. Thanks. Will Shadish
On 8/2/2012 9:49 AM, Simon Wood wrote:
For AIC model comparison, the usual advice applies that although the
comparisons are a bit more reliable for nested models (since then some of
the AIC approximations errors are the same in both cases, and cancel in the
comparison), it is still ok to use AIC for non-nested models (i.e. it is
*not* like most hypothesis testing where everything falls apart if you don't
have nesting).
best,
Simon
--
William R. Shadish
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Chair, Psychological Sciences
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William R. Shadish
University of California
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