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Doing a poisson regression like this: model<-glm(y~x*z,family=poisson) with one predictor being a factor, I would use anova(model,test="Chisq") to test the overall effect of the interaction rather than summary(model), which would give me two interaction terms (one for each of two levels in the factor variable that is not the intercept).

When I do this, I get an output with five columns:

Df, Deviance, Resid. Df, Resid.Dev, Pr(>Chi)

If I do the same with test="F" instead I get an F value, so I assume there is a reason R doesn't report a chi-squared or LRT value.

Is this right? I would have thought that I should report a test statistic with my P value. Can I calculate it from the residual deviance and residual degrees of freedom? Should I report the residual deviance and df with my P value and leave it at that?

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Ben Bolker answers this question in a response to another question here: Comparing nested GLMs via chi-squared and loglikelihood

Apparently, for the purposes of reporting anova(model, test="Chisq") results, the Deviance may be reported as the chi-squared value, though reporting it as Deviance would be more informative.

See also this GLM manual on stat.colombia.edu

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