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Comparison of Decision Tree and Logistic Regression Models for Utilization in Sexual Assault Kit Processing ,
Author(s) -
Wentzlof Chloe A.,
Kerka Jaimie E.,
Albert James H.,
Sprague Jon E.,
Maddox Lewis O.
Publication year - 2019
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/1556-4029.13920
Subject(s) - logistic regression , sexual assault , decision tree , logistic model tree , poison control , human factors and ergonomics , medical emergency , computer science , psychology , medicine , data mining , machine learning
To combat the influx of sexual assault kits ( SAK s) that need to be tested, an exploration of data from Ohio's SAK Testing Initiative was carried out to identify variables that impact whether a SAK contains a probative DNA profile that is eligible for the Combined DNA Index System ( CODIS ) database. A validation study was completed to confirm the existence of variable relationships from the initial examination of data; new and modified statistical models were introduced to improve the predictive accuracy to determine if a SAK will contain at least one CODIS eligible DNA profile. Descriptive statistics from the validation data set confirmed conclusions about the effects of days between the assault and kit collection, the age of the victim, and consensual sex around the time of the kit collection for obtaining CODIS eligibility of DNA . The decision tree was selected as the best model.