I want to compare two GLMs with binomial dependent variables. The results are:
m1 <- glm(symptoms ~ 1, data=data2)
m2 <- glm(symptoms ~ phq_index, data=data2)
The model test gives the following results:
anova(m1, m2)
no AIC logLik LR.stat df Pr(>Chisq)
m1 1 4473.9 -2236.0
m2 9 4187.3 -2084.7 302.62 8 < 2.2e-16 ***
I am used to comparing these kinds of models using chi-squared values, a chi-squared difference, and a chi-squared difference test. Since all other models in the paper are compared this way, and since I'd like to report them in a table together: why exactly is this model test different from my other model tests in which I get chi-squared values and difference tests? Can I obtain chi-squared values from this test?
Results from other model comparisons (e.g., GLMER), look like this:
#Df AIC BIC logLik Chisq Chi DF diff Pr(>Chisq)
m3 13 11288 11393 -5630.9 392.16
m4 21 11212 11382 -5584.9 92.02 300.14 8 0.001