Has anyone looked at it? I'm imagining a situation where you need to bootstrap to get at a quantity of interest, but for whatever reason imputation is the missing data solution of choice.
One could just create the m imputed data sets and draw the bootstrap samples of size n from the overall pool of m*n observations. Does this work? Meaning, have desirable properties? Thanks, Pat -- Patrick S. Malone, Ph.D., Research Scholar Duke University Center for Child and Family Policy Durham, North Carolina, USA e-mail: [EMAIL PROTECTED] http://www.duke.edu/~malone/
