I have this example logit model where some of the variables are factors but I'm not too sure how to interpret the effects. If I understand logit models correctly the coefficients that we get from the fitted model are the change in log-odds per unit change in the explanatory variable holding everything else constant.
If take the
exp() of the coefficients then I have the odds. I'm interested in the impact over the probability of some cathegorical variable to be "male" or "female" for instance. Could you please help me understand this? if
allEffects() is not what I'm looking for, could you please let me know how could I get them?
library(effects) titanic <- glm(survived ~ passengerClass + sex + age,data=Titanic, family=binomial) titanic.all <- allEffects(titanic, typical=median, given.values=c(passengerClass2nd=1/3, passengerClass3rd=1/3, sexmale=0.5)) plot(titanic.all, ticks=list(at=c(.01, .05, seq(.1, .9, by=.2), .95, .99)), ask=FALSE)
EDIT: I don't think it is a duplicate. I'm interested in the output of the package
effects, in particular in the output of the function
I found one document with the following notes "Notice that the print method for the object returned by allEffects reports tables of the effects, which, by default, are on the scale of the response variable, for a logit model, on the probability scale"