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Inclusion Probabilities and Dropout
Author(s) -
Curran James M.,
Buckleton John
Publication year - 2010
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/j.1556-4029.2010.01446.x
Subject(s) - suspect , allele , dropout (neural networks) , inclusion (mineral) , forensic science , psychology , criminology , genetics , statistics , evolutionary biology , biology , computer science , mathematics , social psychology , gene , machine learning
Recent discussions on a forensic discussion group highlighted the prevalence of a practice in the application of inclusion probabilities when dropout is possible that is of significant concern. In such cases, there appears to be an unpublished practice of calculation of an inclusion probability only for those loci at which the profile of interest (hereafter the suspect) is fully included among the alleles present in the crime scene sample and to omit those loci at which the suspect has alleles that are not fully represented among the alleles in the mixture. The danger is that this approach may produce apparently strong evidence against a surprisingly large fraction of noncontributors. In this paper, the risk associated with the approach of ignoring loci with discordant alleles is assessed by simulation.