The AIC (Akaike Information Criterion) penalizes model complexity. Which of the following correctly describes the AIC formula used in SAS model selection?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — you want the formula that uses -2ln(L) + 2k, where -2ln(L) is the deviance and 2k is the penalty for model complexity. Lower AIC means better fit relative to complexity.
Full Explanation
The correct formula is AIC = -2ln(L) + 2k, where k is the number of parameters and L is the maximized likelihood. Here -2ln(L) is the deviance and 2k penalizes complexity; lower AIC means better fit relative to complexity. The 2k + 2 ln(L) version reverses the likelihood sign. The RSS/n + 2k/n formula is a scaled RSS approach like Mallows Cp, not AIC. The BIC - k ln(n) formula conflates AIC with BIC.