Time-Free Effects in Predicting Recidivism Using Both Fixed and Variable Follow-Up Periods: Do Different Methods Produce Different Results
We provide a comparison of analyses used to estimate predictive validity, across fixed (logistic regression and area under the curve receiver operating characteristic [AUC-ROC]) and variable (Cox regression and Harrell’s C) lengths of follow-up. This study adds to research demonstrating a relationsh...
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| Beteiligte: | ; ; |
| Medienart: | Elektronisch Aufsatz |
| Sprache: | Englisch |
| Veröffentlicht: |
[2017]
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| In: |
Criminal justice and behavior
Jahr: 2017, Band: 44, Heft: 1, Seiten: 121-137 |
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Volltext (Resolving-System) |
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| 100 | 1 | |a Flores, Anthony W. |e VerfasserIn |4 aut | |
| 245 | 1 | 0 | |a Time-Free Effects in Predicting Recidivism Using Both Fixed and Variable Follow-Up Periods |b Do Different Methods Produce Different Results |
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| 520 | |a We provide a comparison of analyses used to estimate predictive validity, across fixed (logistic regression and area under the curve receiver operating characteristic [AUC-ROC]) and variable (Cox regression and Harrell’s C) lengths of follow-up. This study adds to research demonstrating a relationship between time at risk offense free and recidivism in two ways. First, reoffending hazard rates were calculated across levels of general offending risk to better understand how failure relates to time at risk. Second, this research compared validity estimates derived from Cox and logistic regression analyses to examine the importance of variable versus fixed follow-up periods. Results show that risk declines as a function of time offense free for all but low risk offenders. In addition, findings demonstrate remarkable stability in estimates of validity after just 7 months of follow-up. Finally, comparisons of Cox and logistic regression analyses, along with their related Harrell’s C and AUC-ROC validity estimates, revealed little substantive differences in prediction | ||
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