Solved – Stepwise model selection using Generalized Akaike Information Criterion

gamlssgeneralized-additive-modelmodel selection

I run a series of models using gamlss stepGAIC() model selection. The problem that I have is that in gamlss, stepGAIC() uses AIC values to select the variables in the model. Since my sample size is considered small I probably need to use the AICc values to select the best model. I don’t know if I would be able to create models using AIC and select from those models the best based on AICc.

Best Answer

In general, you can't select "the best" model using stepwise regression. All statistics produced through stepwise model building have a nested chain of invisible/unstated "conditional on excluding X" or "conditional on including X" statements built into them with the result that:

  • p-values are biased
  • variances are biased
  • parameter estimates are biased
  • F statistics are biased
  • false predictors are likely to be included
  • true predictors are likely to be excluded

So, while you could use AIC as a stepwise model building, the consequences of doing so are unreliable and likely invalid model inferences.

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