# mice: glm.fit: algorithm did not converge

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?