Minimum AIC?! [NCA / SHAM]

posted by Helmut Homepage – Vienna, Austria, 2008-02-03 14:49 (6347 d 05:50 ago) – Posting: # 1575
Views: 29,436

Dear Ohlbe!

❝ What about Akaike's criterion ?


Minimum AIC is only useful in selecting between rival models (e.g., in PK 1 2 compartments, in PD simple Emax sigmoidal Emax).*

For the example we get…
+-----+---------+---------+---------+---------+
|  n  |    3    |    4    |    5    |    6    |
+-----+---------+---------+---------+---------+
| AIC |  7.7894 | 12.3142 | 18.3473 | 20.9395 |
+-----+---------+---------+---------+---------+


… which would suggest n=3 as the ‘best’!
Looking at the definition of AIC
   AIC = n × ln (SSQ) + 2p
it’s clear that since in estimating lambdaz the number of estimated parameters p is fixed to 2 (intercept, slope) AIC essentially reduces to a transformation of the residual sum of squares times the number of data points.
AIC is a quite comfortable in compartmental modeling (as compared to the alternative F-test, because no calculations are needed), but in the given problem it does not help.

❝ I think Kinetica uses it, right ?


At least not in the estimation of lambdaz; strange enough there's a parameter ‘G’ in the output, which is neither described in the online-help nor the manual (v4.1.1, 2007).
I will try to find out the next days, what this parameter might be… :-D



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