[amelia] question about "non-invertible" error

I'm attempting to use AmeliaII in the following way: vars_to_impute <- gundata[,c("progun", "egalitarianism", "individualism", "crfear", "victim", "female", "RACE", "income", "URBANKID", "URBANNOW", "RELIGION", "iss", "democrat", "conservative")] imputed <- amelia(data=vars_to_impute, p2s=2, noms=c("RACE","RELIGION","URBANKID","URBANNOW"), outname="imputation", ords=c("democrat", "conservative") The problem that I run into is that in about half of the imputation attempts fail due to non-invertible covariance matrices. I'm curious if there is any way to deal with this aside from removing the most highly covariant variables? For example, given that it produces imputed data about 1/5 of the time, would it be acceptable to use successful imputations? E.g., can I just set m=100 and use as many imputations as I like from the resulting set of ~25 imputations? If I do need to remove the covariate variables, do you know of a simple way to check for that among a given set of variables?