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.