Abstract

We consider the comparison of hypotheses “parent–child” or “full siblings” against the alternative of “unrelated” for pairs of individuals for whom DNA profiles are available. This is a situation that occurs repeatedly in familial database searching. A decision rule that uses both the kinship index (KI), also known as the likelihood ratio, and the identity-by-state statistic (IBS) was advocated in a recent report as superior to the use of KI alone. Such proposal appears to conflict with the Neyman–Pearson Lemma of statistics, which states that the likelihood ratio alone provides the most powerful criterion for distinguishing between any two simple hypotheses. We therefore performed a simulation study that was two orders of magnitude larger than in the previous report, and our results corroborate the theoretical expectation that KI alone provides a better decision rule than KI combined with IBS.

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