I have a dataset with about 12 categorical variables with levels ranging from 2 - 10, as well as other numerical variables. About 280 records. I'm using the mice package in r to perform imputation on the missing data with all default settings.
However, when I try to do the imputation like this:
imp <- mice(df)
I continue to get this warning:
glm.fit: algorithm did not converge
The solutions I found online here and here only focus on using the glm function directly, but in my case, it's a function that's called from within mice. I've tried setting maxit = 50, like this
imp <- mice(df, maxit = 50)
but only ended up getting many more instances of the same warning. Any idea what could be causing this?
