Advances toward validating examiner writership opinion based on handwriting kinematics. (January 2021)

• Record Type: Journal Article
• Authors: Ommen, Danica M.; Fuglsby, Cami; Caligiuri, Michael P.
• Is Part Of: Forensic science international. Volume 318(2021)
• Publication Date: 2021-01
• Subjects: Handwriting -- Kinematics -- Pen pressure -- Wasserstein score -- Empirical cumulative distribution function -- Scientific validity; Medical jurisprudence -- Periodicals; Chemistry, Forensic -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Chimie légale -- Périodiques; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; Chemistry, Forensic; Medical jurisprudence; Electronic journals; Periodicals; Electronic journals; 614.1
• DOI: 10.1016/j.forsciint.2020.110644
• Languages: English
• ISSNs: 0379-0738

Abstract

Highlights: Study sought to establish scientific validity of FDE writership opinions. Feature dissimilarities and their rarity were highly correlated with FDE opinions. Two-stage regression models added 15% to the predictive value over single-stage models. Findings validate the two-stage process for handwriting evidence interpretation. Abstract: A National Research Council report on strengthening forensic science raised concern over the lack of scientific studies supporting the validity of examining and interpreting forensic evidence. However, establishing the foundational validity of subjective methods can be challenging. The present study aimed to establish the scientific validity of expert writership opinions and the two-stage approach to evidence interpretation using measures derived from research on handwriting motor control. Regression-based procedures were used to address two experimental questions: 1) what are the relative contributions of kinematic and pressure features in predicting examiner support for alternate writership propositions when examining pairs of questioned handwriting samples; and 2) to what extent does information about the rarity of the kinematic feature dissimilarity scores improve the accuracy of a predictive model based on dissimilarity alone. Regarding the first question, we identified a multifactor model consisting of feature dissimilarity scores and their population distributions having correlation coefficients (R 2 ) of 0.84 and 0.88 for the same-writer and different-writers propositions, respectively. Temporal features contributed up to 21% to the predictive value of the model, whereas spatial features contributed only 9% and pen pressure contributed up to 17%. When we compared models reflecting a single-stage process (based on feature dissimilarities) of forming opinions with models reflecting a two-stage process (based on feature dissimilarities and rarity) we found that the two-stage models had an average of 15.25% greater predictive value than single-stage models. These findings support the scientific validity of FDE writership determinations and underscore the importance of the two-stage approach for evidence interpretation.