On ranked set sampling for multiple characteristics

We consider the selection of samples in ranked set sampling when several attributes of each sample are of interest. We describe approaches that have appeared previously in the literature and present a novel method that seeks to achieve samples that are nearly balanced with respect to the ranks of all attributes. This method is shown to result in very little loss of precision compared to problems in which only a single sample attribute is of interest.