Potential bug for mice.impute.polr

[andrewd4vis]

Hello,

I have been working on a simulation study and have been using mice for multiple imputation. I think I have found a bug in mice.impute.polr.

Describe the bug
In some cases I get the following error: Error in apply(draws, 2, sum) : dim(X) must have a positive length

I was able to narrow down this issue and found it only occurred when there was a single missing data point that needs to be imputed for the variable and the proportional log odds model fails and the function resorts to running a multinomial regression as a back up.

I think the error is caused by line 27 converting the post object to a matrix:
if (sum(wy) == 1) {
post <- matrix(post, nrow = 1, ncol = length(post))
}

and then later in the if statement starting on line 32 (which I think is meant to catch cases where just one piece of data is imputed so converts a vector into a matrix):
if (is.vector(post)) {
post <- matrix(c(1 - post, post), ncol = 2)
}

Therefore this leaves the post matrix in incorrect format to then apply the following code, which results in the error:
draws <- un > apply(post, 1, cumsum)
idx <- 1 + apply(draws, 2, sum)

Please let me know if you have any feedback on this issue.