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Using Mixture Models to Examine Group Differences: An Illustration Involving the Perceived Strength of Forensic Science Evidence

This CSAFE webinar was held on December 9, 2021.

Presenter:
Naomi Kaplan-Damary, PhD
The Hebrew University of Jerusalem

Presentation Description:
Forensic examiners compare items to assess whether they originate from a common source. In reaching conclusions, they consider the probability of the observed similarities and differences under alternative assumptions regarding the source(s) of the items (i.e., same or different source). These conclusions can be reported in various ways including likelihood ratios or random match probabilities. Thompson et. al., 2018 examined how lay people perceive the strength of these reports through the use of paired comparison models, obtaining rank-ordered lists of the various statements and an indication of the perceived differences among them. The current study expands this research by examining whether the population is comprised of sub-populations that interpret these statements differently and whether their differences can be characterized. A mixture model that allows for multiple sub-populations with possibly different rankings of the statements is fit to the data and the possibility that covariates explain sub-population membership is considered. A deeper understanding of the way potential jurors perceive various forms of forensic reporting could improve communication in the courtroom.

Associated Reading:
Insights: Using Mixture Models to Examine Group Differences Among Jurors
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