While AIC is a powerful tool, it has certain limitations: 1. Sample Size: AIC can sometimes favor overly complex models, especially in small sample sizes. The corrected version, AICc, is often used when sample sizes are small. 2. Nested Models: AIC does not provide information on whether a simpler model is nested within a more complex model, which can sometimes be important in epidemiological studies. 3. Assumptions: AIC assumes the models being compared are correctly specified and that the data come from a stationary process.
