I have a data set that looks like this (subset below):

ID  Treatment  Mortality
1    A         0
2    A         0
3    A         0
4    A         0
5    B         0
6    B         1
7    B         1
8    B         0
9    C         0
10   C         0
11   D         0
12   D         1

and I ran the following GLM to examine the effects of treatment on mortalitiy:

model <- glm(Mortality ~ Treatment, family = binomial, data = data)

I checked the model for overdispersion and it was not overdispersed, as the residual deviance was less than the degrees of freedom. However, I'm having trouble finding resources that list the other assumptions of this type of GLM (logistic regression with categorical predictor variables).

What are the assumptions and how do I test them and the model fit?

  • $\begingroup$ Related $\endgroup$
    – Dave
    Aug 30 at 19:43


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