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so I am using GLM for logistic regression in R and I have some variables with many factors.

I ran the model and has the result like this:

enter image description here

My question is: 1. Is this variable significant? Considering only Married and Separated are significant here (p-values <0.05). What about if there are 10 different categories for a variable, but only 3 of them are significant? Should I drop it or keep it in the model?

  1. Also, in the case of a model where all the variables are significant but the AIC value is much higher than the one where a variable included is not significant, which one is more useful? What can cause this?
kjetil b halvorsen
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user71812
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    You should employ some knowledge about the research matter. Depending on what is studied there, it might make sense to group married and widow together or maybe not. Use anova output to judge if the factor variable is significant. If you have many factor levels, you could try dimension reduction techniques. Or it might make sense to model this as a random effect. Not enough information provided and it's off-topic anyway. Voting to close. – Roland Aug 01 '19 at 07:52
  • @Roland Regarding random effects, I think it's generally recommend to have quite a bit more than 4 levels. – mkt Aug 02 '19 at 05:28
  • @mkt Yes, and the previous sentence mentions having many factor levels. – Roland Aug 02 '19 at 05:50
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    @Roland Ah, I initially didn't read that as applying to your random effect recommendation as well. – mkt Aug 02 '19 at 05:57

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