I am trying to fit my data to a distribution and find the fit parameters and associated p-value. If I use the -2-log likelihood ratio, or G-test, vs the minimum deviance method, will I get different p-values?

Using the minimum deviance method, once I get the minimum deviance statistic, I use the chi-square test.

I am wondering whether I should be getting the same p-values using both tests, or is it justified that when using the minimum deviance method, my p-values are generally larger than when using the -2-log likelihood ratio?


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