The authors considered 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. The authors therefore performed a simulation study that was two orders of magnitude larger than in the previous report, and their results corroborated the theoretical expectation that KI alone provides a better decision rule than KI combined with IBS. (Published Abstract)
Similar Publications
- Positive Identification Using Frontal Sinus Comparisons: Developing Empirically Based Guidelines
- Improving and Evaluating Computed Tomography and Magnetic Resonance Imaging in the Investigation of Fatalities Involving Suspected Head Trauma
- Enhancing Fault Ride-Through Capacity of DFIG-Based WPs by Adaptive Backstepping Command Using Parametric Estimation in Non-Linear Forward Power Controller Design