Theses and Dissertations
Date of Award
4-2-2026
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Abraham S. Fischler College of Education and School of Criminal Justice
Advisor
Steven Hecht
Committee Member
Marcelo Castro
Committee Member
Alexander Toth
Committee Member
Tammy Kushner
Keywords
benchmarks, classification, Cohen’s d, CrimeSolutions, criminal justice research, effect size, effect size benchmarks, effect size classification, empirical benchmarks, intervention effectiveness, meta-analysis, percentile-based methods, policymaking, quasi-meta-analysis, statistical validity, violent crime, violent crime interventions
Abstract
Criminal justice researchers apply Cohen’s (1988) benchmarks to classify effect sizes as small, medium, or large, despite these standards never being meant for broad, decontextualized use (Cohen, 1988; Gies et al., 2024; Goulet-Pelletier & Cousineau, 2018; Lakens, 2013; Milner et al., 2023). Repeatedly doing so may weaken statistical validity, distort findings, and impede effective policymaking. This study introduces the first effect size benchmarks specifically designed for violent crime interventions.
Using a quasi-meta-analysis framework, 1,605 effect sizes from 104 violent crime intervention studies from the CrimeSolutions clearinghouse were converted to Cohen’s d. Three new discrete benchmarking methods were created using a tailored version of Cohen’s benchmarks (Cohen, 1988), tertiles (Gies et al., 2024; Hemphill, 2003; Lipsey & Wilson, 1993; Meyer et al., 2001), and quartiles (Lovakov & Agadullina, 2021; Milner et al., 2023; Panjeh et al., 2023; Tanner-Smith et al., 2018).
Results suggest that Cohen’s (1988) benchmark underestimates effects and overclassifies them as small. Interpretations of effect sizes are affected by benchmarking methodology, the category of violent crime, and size classification. Researchers do not regularly report effect sizes; instead, they usually present statistical test values or raw means and standard deviations. Significant differences in classification proportions were observed between Cohen-based and percentile-based methods.
These findings question the use of Cohen’s (1988) benchmark for violent crime interventions and offer empirically grounded alternatives for interpreting effect sizes that might otherwise be considered insignificant or undervalued. With a better understanding of the magnitude of interventions, policymakers can prioritize more effective programs (Gies et al., 2024; Tanner-Smith et al., 2018).
NSUWorks Citation
Kohta James Matsukawa Hansen. 2026. Empirical Benchmarks for Interpreting Effect Sizes in Violent Crime Interventions. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, Abraham S. Fischler College of Education and School of Criminal Justice. (1195)
https://nsuworks.nova.edu/fse_etd/1195.