Mixed Group Validation (MGV) is an approach for estimating the diagnostic accuracy of tests. MGV is a promising alternative to the more commonly used Known Groups Validation (KGV) approach for estimating diagnostic accuracy. The advantage of MGV lies in the fact that the approach does not require a perfect external validity criterion or gold standard. However, the research designs where MGV is most appropriate have not been thoroughly explored. We give a brief description of the ideal research design to minimize error for MGV studies, test whether the MGV assumptions hold with clinical data, evaluate whether there is evidence of assumption violation among published MGV studies, give a practical description of the MGV assumptions, and describe an example of an optimal use of MGV. Ultimately, we conclude that MGV is not generally superior to KGV but may be used in some cases where the assumptions and standard error have been considered appropriately. (Contains 7 tables and 1 figure.)