Investigating the Functional Form of the Self-control-Delinquency Relationship in a Sample of Serious Young Offenders



Christopher J. Sullivan, Thomas Loughran

Journal of Quantitative Criminology

March 2014




This work further examines the functional form of the self-control–delinquency relationship as an extension of recent work by Mears et al. (J Quant Criminol, 2013). Given the importance of the authors’ conclusions regarding the nonlinear relationship between these two variables and the recognition that there are some potential limitations in the sample and assumptions required for the analytic methods used, we apply both similar and alternative techniques with a data set comprised of serious youthful offenders to determine whether key findings can be replicated.


Data from the Pathways to Desistance study, which comprise extensive individual and social history interviews with 1,354 offenders over multiple waves spread out over 84 months, is utilized in this analysis. These data are well-suited to investigating the questions of interest as the target population comprises youth with offending histories that are more extensive than those likely to be found in general surveys of adolescents. The analyses consider the self-control–delinquency relationship in an alternative sample with the previously used Generalized Propensity Score (GPS) procedure, which requires strong assumptions, as well as nonparametric regression which requires far weaker assumptions to consider the functional form of the self-control–delinquency relationship.


The results generally show that the identified functional form of the self-control–delinquency relationship seems to be at least partly dependent on aspects of the modeling of dose–response associated with GPS procedures. When nonparametric general additive models are used with the same data, the relationship between self-control and delinquency seems to be approximately linear.


Identifying functional form relationships has importance for many criminological theories, but it is a task that requires that the balance of model assumptions to exploratory data analysis falls toward the latter. Nonparametric approaches to such questions may be a necessary first step in learning about the nature of mechanisms presumed to be at work in important explanations for crime and criminality.