This article presents analytic methods and accompanying computational tools for estimating the expected quality and diversity outcome of general multistage selections when the applicant pool is a finite, typically small sample from a mixture of majority and minority applicant populations. The new methods generalize the analytic estimation of the expected quality of small heterogeneous applicant pool selections from simple, single-stage selection situations to the more general, multistage selection context. In addition, the new methods also compute the sampling variability of the selection quality outcome for these selection decisions.
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