Using subsampling to estimate the strength of handwriting evidence via score-based likelihood ratios.
The likelihood ratio paradigm has been studied as a means for quantifying the strength of evidence for a variety of forensic evidence types. Although the concept of a likelihood ratio as a comparison of the plausibility of evidence under two propositions (or hypotheses) is straightforward, a number of issues arise when one considers how to go about estimating a likelihood ratio. In this paper, we illustrate one possible approach to estimating a likelihood ratio in comparative handwriting analysis. The novelty of our proposed approach relies on generating simulated writing samples from a collection of writing samples from a known source to form a database for estimating the distribution associated with the numerator of a likelihood ratio. We illustrate this approach using documents collected from 432 writers under controlled conditions.
Department of Statistics (MS 4A7), George Mason University, Fairfax, VA 22030, USA. ldavisc@gmu.edu
Linda J
LJ
Davis
Christopher P
CP
Saunders
Amanda
A
Hepler
JoAnn
J
Buscaglia
D000465:Algorithms; D044707:Forensic Sciences; D006236:Handwriting; D006801:Humans; D016013:Likelihood Functions