[R-sig-eco] Corrected AIC for binary response variables? (Landis, R Matthew)

[Murray Efford]

Matt Landis asked
>>I'm using logistic regression to investigate mortality of trees.  I'm using AIC to compare models, and I'm wondering if I should use AICc instead of  AIC.  Burnham and Anderson [1] recommend using AICc when n/K < 40.  But what do I consider for n?  The logistic regression is based on 2811 observations (334 trees observed annually for <= 10 yr), but I've only observed 32 deaths.  Harrell [2] would consider 32 to be the "limiting sample size" for determining the feasible number of predictor variables.  Is AIC the same?  Should I use 2811, 334, or 32 to figure out AICc?

You may be interested in an exchange on this topic that I initiated on www.phidot.org/forum MARK Statistics & analysis help on 30 September. I found the outcome quite unsatisfactory, and it seems the experts don't know. 334 seems safe to me, and of course it will make little numerical difference.

Murray Efford

[I'm sorry that I have this through the Digest & my reply may not conform]