Answering the career criminal debate: Comparing finite mixture modeling with growth mixture modeling.

The article highlights the characteristics of chronic criminals. It presents a comparison of finite mixture modeling with growth mixture modeling. FMM is defined as ideal statistical framework for longitudinal studies of delinquency where the number of delinquent acts committed each year by each member of the sample is the dependent variable of interest. There is a growing body of literature that predicts that it is the high-rate adolescent offenders that benefit the most from prevention programs and intervention programs. Successful identification of risk factors linked with the development of criminality can lead to successful prevention and intervention.