I'm fitting a model in R where response variable is an over-dispersed count data, and where I meet an issue with goodness-of-fit test. As it has been previously discussed in Cross Validated, common GOF test like chi-square test for deviance is inappropriate for negative binomial regression because it includes a dispersion parameter as well as the mean:
https://stats.stackexchange.com/questions/504616/appropriate-goodness-of-fit-test-for-the-negative-binomial-regression
I'm confused and would appreciate any suggestions about the appropriate GOF test for NB regression (preferably intuitive).
The Likelihood Ratio Chi-Square test is the appropriate goodness-of-fit test for negative binomial regression. This test compares the fit of the negative binomial regression model to an alternative model, typically a simpler model such as a Poisson regression.
To perform the Likelihood Ratio Chi-Square test for negative binomial regression in SPSS, you can follow these steps:
It's important to note that the Likelihood Ratio Chi-Square test assesses the overall goodness-of-fit of the negative binomial regression model but does not provide information about specific predictors or individual model assumptions. Additional diagnostic tests and assessments should be performed to evaluate the model's performance thoroughly.
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