Date of Award

Fall 12-2019

Document Type

Thesis

Degree Name

Master of Science (MS)

Department/Program

Forensic Science

Language

English

First Advisor

Mechthild Prinz

Second Reader

Nicholas D.K. Petraco

Third Advisor

Adele Mitchell

Abstract

Complex DNA mixtures can be very probative evidence, but comparisons to a person of interest can be affected by allelic drop-out and uncertainty regarding the number of individuals having contributed DNA to a sample. Scientific organizations such as the International Society of Forensic Genetics (Gill et al., 2006) recommend that likelihood ratios should be used to provide a statistical weight when a positive association is made between the DNA profile of a person of interest and an evidentiary DNA sample. To this effect the New York City Office of Chief Medical Examiner (OCME) developed a software program, Forensic Statistical Tool (FST), which calculates likelihood ratios for different scenarios taking into account empirically developed drop-out and drop in rates for different types of mixtures. The FST software was used to explore the effect of underestimation of a contributor’s true drop-out rate and effect of the incorrect estimation of the number of contributors on LR calculations. It was found that underestimating the allelic dropout rate for a true contributor almost always led to an either equal or lower LR than when the original dropout rate was used. It was also found that when the number of contributors was misspecified, there was an increase or decrease in LR values for true contributors. Variation of resulting LRs was higher for more complex mixtures. Finally, LRs for comparisons to individuals, whose DNA was known to not be present in the test mixtures, were lower when using the lower drop-out rates than when using the true drop-out rates.

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