Exploring the Black Box of Community Supervision

Bonta, James; Rugge, Tanya; Scott, Terri-Lynne; Bourgon, Guy; Yessine, Annie K.

doi:10.1080/10509670802134085

Cited by 289 publications

(353 citation statements)

References 9 publications

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“…For example, in the criminal justice field, they are often used to index the relationship between risk factors or risk scales with dichotomously defined recidivism (e.g., Andrews & Bonta, 2010;Olver, Wong, Nicholaichuk, & Gordon, 2007;Rice, Harris, & Lang, 2013). Similarly, meta-analyses on the prediction of recidivism or other dichotomous outcomes frequently use correlations as their effect size (Andrews et al, 1990;Bonta, Rugge, Scott, Bourgon, & Yessine, 2008;Campbell, French, & Gendreau, 2009;French & Gendreau, 2006;Gendreau, Little, & Goggin, 1996;Gonçalves, Gonçalves, Martins, & Dirkzwager, 2014). Correlations with dichotomous or ordinal data also appear as intermediate steps in other analyses, such as factor analyses of measures with dichotomous or ordinal scale items.…”

Section: Introductionmentioning

confidence: 99%

The influence of base rates on correlations: An evaluation of proposed alternative effect sizes with real-world data

Babchishin

Helmus²

2015

Behav Res

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Correlations are the simplest and most commonly understood effect size statistic in psychology. The purpose of the current paper was to use a large sample of real-world data (109 correlations with 60,415 participants) to illustrate the base rate dependence of correlations when applied to dichotomous or ordinal data. Specifically, we examined the influence of the base rate on different effect size metrics. Correlations decreased when the dichotomous variable did not have a 50 % base rate. The higher the deviation from a 50 % base rate, the smaller the observed Pearson's point-biserial and Kendall's tau correlation coefficients. In contrast, the relationship between base rate deviations and the more commonly proposed alternatives (i.e., polychoric correlation coefficients, AUCs, Pearson/Thorndike adjusted correlations, and Cohen's d) were less remarkable, with AUCs being most robust to attenuation due to base rates. In other words, the base rate makes a marked difference in the magnitude of the correlation. As such, when using dichotomous data, the correlation may be more sensitive to base rates than is optimal for the researcher's goals. Given the magnitude of the association between the base rate and point-biserial correlations (r = −.81) and Kendall's tau (r = −.80), we recommend that AUCs, Pearson/Thorndike adjusted correlations, Cohen's d, or polychoric correlations should be considered as alternate effect size statistics in many contexts.

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Section: Introductionmentioning

confidence: 99%

The influence of base rates on correlations: An evaluation of proposed alternative effect sizes with real-world data

Babchishin

Helmus²

2015

Behav Res

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“…However, evidence suggests that in practice the coherence between the risk and needs assessment and the intervention plan is not a straightforward matter. In a study of offender supervision for example, Bonta and colleagues found that much of the information obtained from the assessment was not used in the intervention plan (Bonta et al 2008). Vieirra and colleagues investigated the match between the assessed needs and the services received through probation.…”

Section: Introductionmentioning

confidence: 99%

Do Intervention Plans Meet Criteria for Effective Practice to Reduce Recidivism? How Probation Officers Forget about Social Capital and Basic Needs

Bosker¹,

Witteman²,

Hermanns³

2013

European Journal of Probation

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“…Significant concerns have, however, also been expressed about both the quality and the effectiveness of rehabilitation programs, with doubts being raised about the integrity of rehabilitative practice, reflecting the gap that sometimes exists between stated policy and the way it is implemented (e.g., Andrews 2006;Bonta et al 2008). Smith et al (2009: 162) have, for example, suggested that program effectiveness is often "compromised by staff drift and organisational resistance at both the frontline and administrative levels".…”

Section: Introductionmentioning

confidence: 99%