Progress Toward the Determination of Correct Classification Rates in Fire Debris Analysis II: Utilizing Soft Independent Modeling of Class Analogy (SIMCA)

• Published in: Journal of forensic sciences 2014-07, Vol.59 (4), p.927-935
• Main Authors: Waddell, Erin E., Williams, Mary R., Sigman, Michael E.
• Format: Article
• Language: English
• Subjects: chemometrics; Classification; fire debris; Fires; forensic science; Forensic sciences; gas chromatography-mass spectrometry; multivariate statistics; soft independent modeling of class analogy; Solvents
• ISSN: 0022-1198; 1556-4029
• DOI: 10.1111/1556-4029.12417

A multistep classification scheme was used to detect and classify ignitable liquid residues in fire debris into the classes defined by the ASTM E1618‐10 standard method. The total ion spectra (TIS) of the samples were classified by soft independent modeling of class analogy (SIMCA) with cross‐validation and tested on fire debris. For detection of ignitable liquid residue, the true‐positive rate was 94.2% for cross‐validation and 79.1% for fire debris, with false‐positive rates of 5.1% and 8.9%, respectively. Evaluation of SIMCA classifications for fire debris relative to a reviewer's examination led to an increase in the true‐positive rate to 95.1%; however, the false‐positive rate also increased to 15.0%. The correct classification rates for assigning ignitable liquid residues into ASTM E1618‐10 classes were generally in the range of 80–90%, with the exception of gasoline samples, which were incorrectly classified as aromatic solvents following evaporative weathering in fire debris.