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Jan 24, 2013 4:52 PM
(388 views)

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Feb 1, 2013 8:41 AM
(208 views)

Think about what a p value is--the probability that a null hypothesis is rejected is usually the answer given. But it has some assumptions, the first being that some sort of test exists. About the only test I can think of is a likelihood ratio test, comparing the log-likelihoods of the model that is fit, to the null model. It turns out, that for reasonably sized datasets and a limited number of model parameters, AICc is as good a comparator as you can find. However, the chi-square value from comparing the -2 log-likelihoods is the only "p value" generating test that I can think of.

Steve Denham