Generalized symmetric means are redefined in a way which allows them to be calculated for any matrix sampling design. It is proved that these sample generalized symmetric means are unbiased estimates of the analogous population generalized symmetric means. Illustrative examples are given. (Author)

A single conceptual and theoretical framework for sampling any configuration of data from one or more population matrices is presented, integrating past designs and discussing implications for more general designs. The theory is based upon a generalization of the generalized symmetric mean approach for single matrix samples. (Author/CTM)