For my data set, I have to generate confidence bands for a number of parameters. I already did empirical bootstrapping via the function umxCI_boot from the package 'umx'. My data set contains a number of missing values (with FIML used for the model estimation) so when I did empirical bootstrapping, it stated a warning indicating the presence of missing values in the observed covariance matrix, making it non-positive-definite so the empirical bootstrapping did not proceed.
My question is: What would be the next sensible thing to do? Use parameteric Monte-Carlo bootstrapping instead based on the expected covariance matrix? With the observed covariance matrix containing missing values, doing parametric Monte-Carlo bootstrapping on it might be futile.
Thank you for your feedback.