[R] question about logistic models (AIC)

Kyle Ambert ambertk at ohsu.edu
Fri Aug 3 19:48:29 CEST 2007

```Ah.  Very good point.  I stand corrected.

---Kyle.

>>> ted.harding at nessie.mcc.ac.uk 08/03/07 10:32 AM >>>
On 03-Aug-07 16:42:33, Kyle. wrote:
> Tom:
>
> That's a good question.  AIC, as i'm sure you know, is usually
> calculated as 2k-2ln(L), where k is the number of free parameters in
> the model, and L is the log-likelihood of the model.  The goal of
> AIC--and the reason one normally tries to select a model with minimal

> AIC--is to minimize what's referred to as the Kullback-Leibler
> distance between the distribution of your data's density from the
> theoretical "true" theoretical density as defined by the model.  More

> concisely, the AIC is an index of the amount of information regarding

> your data that is lost when your model is used to describe it.  To
> get back to your question, I can't say without a little more
> information why the AIC's your referring to are negative (but perhaps

> it's an issue of using the log-likelihood instead of the negative log-

> likelihood), but my first instinct is that it doesn't matter.  I
> would go with the AIC that is closest to zero.  I hope that helps.

That could be wrong! Don't forget that ln(L) is indeterminate to
within an additive constant (for given data), so one man's negative
AIC could be another mans positive AIC -- but if each compared
their AICs with different models (the same different models for each)
then they should get the same *difference* of AIC.

The correct approach is to compare AICs on the basis of algebraic
difference: AIC1 - AIC2 in comparing Model1 with Model2.

If this is positive then Model2 is better than Model1 (on the AIC
criterion). Taking "the AIC that is closest to zero" would be the
wrong way round for negative AICs.

Ted.

> On Aug 3, 2007, at 8:41 AM, Tom Willems wrote:
>
>> Dear fellow R-ussers,
>> I have a question about the Akaike Information Criterion  in the  R
>> output.
>> Normally you would want it to be as small as possible, yet when i
>> check up the information in my study books, the AIC is usually
>> displayed as a negative number. In the exercises it is given as
>> " - AIC ".
>> R displays it as a positive number, does this mean that a large "AIC"
>> gives a small " - AIC ", so the bigger the better?
>>
>> Kind regards,
>> Tom.
>>
>> Tom Willems
>> CODA-CERVA-VAR
>> Department of Virology
>> Epizootic Diseases Section
>> Groeselenberg 99
>> B-1180 Ukkel
>>
>> Tel.: +32 2 3790522
>> Fax: +32 2 3790666
>> E-mail: towil at var.fgov.be
>>
>> www.var.fgov.be

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E-Mail: (Ted Harding) <ted.harding at nessie.mcc.ac.uk>
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Date: 03-Aug-07                                       Time: 18:31:51
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