title: Identifying Male Sexual Offender Subtypes Using Cluster Analysis and the Static-2002R.
abstract: This study examines whether clinically meaningful subgroups could be identified within a large, undifferentiated group of convicted adult male sex offenders. Of eight cluster analyses, a reliable three-cluster solution emerged based on the subscores of the Static-2002R with 345 sex offenders. To establish the validity of the emergent clusters, the three groups of offenders were compared on four domains: criminal history, psychosexual development, sexual attitudes and interests, and recidivism. The findings revealed meaningful differences among the group, and the implications of subgroup membership is discussed in terms of risk, treatment, and supervision.
authors.affiliation: Integrated Threat and Risk Assessment Centre, Alberta Law Enforcement Response Teams, Edmonton, Alberta, Canada liam.ennis@alert-ab.ca.
authors.forename: Liam
authors.initials: L
authors.lastname: Ennis
authors.affiliation: MacEwan University, Edmonton, Alberta, Canada.
authors.forename: Karen
authors.initials: K
authors.lastname: Buro
authors.affiliation: MacEwan University, Edmonton, Alberta, Canada.
authors.forename: Sandy
authors.initials: S
authors.lastname: Jung
mesh_terms: D000328:Adult; D016000:Cluster Analysis; D000066479:Criminal Behavior / Q000145:classification*; D057237:Criminals / Q000145:classification*; D006801:Humans; D008297:Male; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D012742:Sex Offenses / Q000145:classification*
keywords: RNR; cluster analysis; criminogenic factors; risk assessment; sex offenders; subtypes