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Importance Sampling Allows H-d True Tests of Highly Discriminating DNA Profiles

NCJ Number
Date Published
March 2017
8 pages
This article describes the use of importance sampling, which enables the simulation of rare events to occur more commonly than they would at random, and then adjusting for this bias at the end of the simulation in order to recover all diagnostic values of interest; the advantages of using it and its application to Hd true tests are explained.
Hd true testing is a way of assessing the performance of a model, or DNA profile interpretation system. These tests involve simulating DNA profiles of non-donors to a DNA mixture and calculating a likelihood ratio (LR) with one proposition postulating their contribution and the alternative postulating their non-contribution. Following Turing, it is possible to predict that “The average LR for the Hd true tests should be one.” This suggests a way of validating softwares. During discussions on the ISFG software validation guidelines, it was argued by some that this prediction had not been sufficiently examined experimentally to serve as a criterion for validation. More recently a high profile report has emphasized large-scale empirical examination. A limitation with Hd true tests, when non-donor profiles are generated at random (or in accordance with expectation from allele frequencies), is that the number of tests required depends on the discrimination power of the evidence profile. If the Hd true tests are to fully explore the genotype space that yields non-zero LRs, then the number of simulations required could be in the 10 s of orders of magnitude (well outside practical computing limits). Importance sampling, although having been employed by others for Hd true tests, is largely unknown in forensic genetics. This article concludes by showing that employing an importance sampling scheme brings Hd true testing ability to all profiles, regardless of discrimination power. (Publisher abstract modified)

Date Published: March 1, 2017