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Abstract
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OBJECTIVES This paper addresses a central problem in general strain theory (GST): the mixed results regarding those factors said to condition the effect of strains on crime. We test Agnew's (Deviant Behav 34(8):653-670, 2013) assertion that a criminal response to strain is likely only when individuals score high on several factors that increase the propensity for criminal coping or possess markers that indicate a strong propensity for criminal coping.
METHODS We use survey data from nearly 6000 juveniles from across the United States to examine whether the effect of criminogenic strains across several domains--perceptions of police, school environment, and victimization--on crime are conditioned by: (1) respondents' criminal propensity and (2) gang membership. To the best of our knowledge, this is the first criminological study to employ an analytical framework that simultaneously considers nonlinear (i.e., curvilinear) dynamics, non-additive (i.e., interactive) effects, and non-normally distributed dependent variables. This approach has the advantage of properly differentiating nonlinear and non-additive dimensions and therefore significantly improving our understanding of conditioning effects.
RESULTS We find considerable support for Agnew's (2013) postulation about conditioning effects and GST. Criminal behavior is more likely among those with a strong overall propensity for criminal coping and among gang members. Furthermore, we discover that the conditioning effects are, themselves, nonlinear. That is, the effect of criminal propensity on moderating the relationship between our three measures of strain and delinquency varies across the range of the criminal propensity index. Our models that simultaneously consider both the non-additive and nonlinear relationship between strains, criminal propensity, and criminal offending better fit the data than models that consider these dimensions separately. These results hold whether examining a composite measure of criminal activity or, alternatively, three separate subscales indexing violent, property, and drug offenses.
CONCLUSION Our study advances GST and the crime literature by identifying the types of strained individuals most likely to engage in criminal coping. Additionally, the analytical framework we adopt serves as a model for the correct measurement and interpretation of conditioning effects for criminological data, which almost invariably violate the assumptions of the linear regression model. Parametric interactions are the most commonly investigated type of interactions, but other kinds of interactions are also plausible and may reveal conditional relationships that are either overlooked or understated when analysts adopt a fully parametric framework. We demonstrate the utility of expressly modeling both the nonlinear effects of component variables in an interaction and the nonlinear nature of the conditioning effect.
Language: en |