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How do I check my AIC in R?
Details. AIC = – 2*log L + k * edf, where L is the likelihood and edf the equivalent degrees of freedom (i.e., the number of parameters for usual parametric models) of fit . For generalized linear models (i.e., for lm , aov , and glm ), -2log L is the deviance, as computed by deviance(fit) .
Can we use R Squared to compare models?
Don’t use R-Squared to compare models This is, as a pretty general rule, an awful idea. In many situations the R-Squared is misleading when compared across models. Examples include comparing a model based on aggregated data with one based on disaggregate data, or models where the variables are being transformed.
Do you need a nested likelihood ratio test?
That’s a lot of models. If you’ve ever learned any of these, you’ve heard that some of the statistics that compare model fit in competing models require that models be nested (specifically, the likelihood ratio test, based on model deviance). This is particularly important while you’re trying to do model building.
What does non nested model selection mean in AIC?
In the case of model selection, generally (but not always) that means some of the parameters equal zero. If the models are nested, the parameters in the larger model that are not in the smaller model are the ones being tested, with values specified implicitly by their exclusion from the smaller model.
Why do we need to use nested models?
If you’ve ever learned any of these, you’ve heard that some of the statistics that compare model fit in competing models require that models be nested (specifically, the likelihood ratio test, based on model deviance). This is particularly important while you’re trying to do model building. You need to know which model fits better.
When to use LRTs to compare two nested models?
LRTs are generally used to compare two nested models – i.e. in situations where one of the models is a special case of the other – with the null hypothesis that the data are drawn from the simpler of the two models. It is often assumed that LRTs can only be used to compare nested models.