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A Sensitivity Analysis To Determine the Robustness of STRmix (TM) With Respect to Laboratory Calibration

NCJ Number
253282
Date Published
July 2018
Length
10 pages
Author(s)
Hannah Kelly; Jo-Anne Bright; Maarten Kruijver; Stuart Cooper; Duncan Taylor; Kyle Duke; Melissa Strong; Vickie Beamer; Christina Buettner; John Buckleton
Agencies
NIJ-Sponsored
Publication Type
Research (Applied/Empirical), Report (Study/Research), Report (Grant Sponsored), Program/Project Description
Grant Number(s)
2017-DN-BX-0136
Annotation
Since STRmix uses several laboratory-specific parameters to calibrate the stochastic model for peak heights, and these are modelled on empirical observations specific to the instruments and protocol used in the analysis, the current study used a sensitivity analysis to assess the extent to which these parameters can be borrowed from laboratories with similar technology and protocols without affecting the accuracy of the system.
Abstract
Parameters were first calibrated to a publicly available dataset, after which a large number of likelihood ratios were computed for true contributors and non-contributors, using both the calibrated parameters and several borrowed parameters. Differences in the LR caused by using different sets of parameter values were found to be negligible. (publisher abstract modified)
Date Created: July 20, 2021