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Author: Coyne, Michelle A.
Resulting in 1 citation.
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Coyne, Michelle A. |
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Predicting Arrest Probability Across Time: A Test of Competing Perspectives Ph.D. Dissertation, Department of Criminal Justice, University of Cincinnati, 2015 Cohort(s): NLSY97 Publisher: ProQuest Dissertations & Theses (PQDT) Keyword(s): Arrests; Crime; Delinquency/Gang Activity; Modeling, Latent Class Analysis/Latent Transition Analysis Permission to reprint the abstract has not been received from the publisher. Criminal involvement is non-randomly distributed across individuals and across groups. Debate regarding the etiology of differences in criminal involvement remains. Using data from the National Longitudinal Survey of Youth 1997, the current study examined latent class membership in the probability of arrest over a 15-year time span starting when participants were 12-16 years-old and ending when they were 28-31 years-old. Latent class regressions were employed to prospectively investigate whether various demographic and criminological risk factors from the base wave could predict class membership. Models were also estimated separately by sex and by race to identify potentially important differences and consistencies in class structure and risk prediction. Results from the latent class growth analyses resulted in two to three classes characterized by an abstainer group, an adolescent-limited group, and a stable moderate-level chronic group. In general, being male, increased substance use, and increased delinquency were consistent predictors of class membership. Regarding race and sex differences, being a minority was moderately related to class membership in males but was not significant for females. Being male was a very strong predictor of class membership for Black and Hispanic participants but a relatively weak predictor for White participants. Overall, results supported a general risk factor perspective over a gender or race specific risk perspective. Across race, sex, and cohort, self-reported delinquency was the strongest risk predictor of class membership, suggesting that differential arrest probability is predominantly explained by differential involvement in delinquent behavior. |
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Bibliography Citation
Coyne, Michelle A. Predicting Arrest Probability Across Time: A Test of Competing Perspectives. Ph.D. Dissertation, Department of Criminal Justice, University of Cincinnati, 2015. |