I have two nested nonlinear models and I want to know which provides a better fit to some data. I see descriptions of both the likelihood ratio test and of the incremental F-test (also called the nested F-test or the extra sum-of-squares F-test) but I cannot find any discussion of when you would use one or the other or their relative advantages/disadvantages.

Can anyone enlighten me?


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