Hi Bonnie,
Here is an excellent link that explains
the AIC (you are looking for the lowest value for
AIC).
http://www.theses.ulaval.ca/2004/21842/apa.html
You might want to look at other criteria such as BIC,
AICc, HQ, HQc, FPE etc. (you might want to look at
Regression and Time Series Model Selection by
McQuarrie and Tsai (1999) - World Scientific for more
detail.
Hope this helps. Paul
Paul Johnson
http://www.biostatsoftware.com
--- bonnie clark <[EMAIL PROTECTED]> wrote:
> Im getting conflicting answers to a question and am
> hoping you could help.
>
> When using the Akaike Information Criterion (AIC),
> am I looking for the
> smallest number or the smallest absolute number?
>
> For example, I have two models.
>
> (-2 log likelihood) + (2k)
>
> log likelihood k AIC
>
> 532.5052 16 -1033.0104
> 509.8392 58 -903.6784
>
> the difference between the two is great, but which
> is better?
> -1033.0104 is the smallest, but -903.6784 is the
> smallest absolute value.
>
> I wont say which model I LIKE better. =)
>
> thanks,
> bc
>
>
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