My data is ordinal, and so missing values are imputed with the polr method from the MICE package. Now I have multiple datasets which I can run an Ordinal Logistic Regression on. But, as the title mentioned: I want to perform a Brant test to check the parallel regression assumption. How can I perform such a test on my imputed datasets?
olr <- with(imputed, polr(target ~ var1+var2)) olrsummary <- summary(pool(olr)) > brant(olr) Error in formula.default(model) : invalid formula > brant(olrsummary) Error in temp.data[, name] : incorrect number of dimensions
I know I can take the first dataset with complete(imputed, 1) and use that for my Brant test. But that just don't sees right.