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Predicting Rapist Type from Crime-Scene Variables

Brandeis University

JANET I. WARREN

University of Virginia

ROLAND REBOUSSIN

FBI Academy

BONITA J. SOLEY

Brandeis University

Secondary data analyses on two analogous data sets assessed the ability of crime-scene variables observed in serial rapes to predict classification in the Massachusetts Treatment Center, Rapist Typology Version 3 (MTC:R3). Data sets from the FBI containing extensive coding of crime-scene information but minimal offender data were analyzed to select optimal predictors by examining the frequencies and both within-crime and across-crime consistencies of crime-scene indicators. Analogous predictors were identified in the MTC database, which contains extensive offender data but minimal crime-scene data, and these indicators were employed to predict rapist type. Promising predictive results emerged in the domains of adult antisocial and expressive aggression. In addition, the domains of sadism, offense planning, and relation with victim showed high internal consistency and good to high cross-crime consistency, suggesting that predictive scales are possible for these domains.

Criminal Justice and Behavior, Vol. 25, No. 1, 46-80 (1998)
DOI: 10.1177/0093854898025001004


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