The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

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0. No 1. Yes C15. Random assignment to conditions? rassgt 0. No 1. Yes C16. Measurement <strong>of</strong> prior criminal involvement? prior 0. No 1. Yes C17. Rating <strong>of</strong> initial similarity between treatment and control group: prsim 1 2 3 4 5 6 7 (1 = Nonrandomized; high likelihood <strong>of</strong> baseline differences between groups or known differences related to future recidivism) (5 = Nonrandomized design with strong evidence <strong>of</strong> initial equivalence) (7 = Randomized design with large N or small N design with matching) C18. Was attrition discussed in the report? attrep 0. No 1. Yes C19. Is there a potential threat to generalizability from overall attrition? attgen 0. No 1. Yes C20. Is there a potential threat to internal validity from differential attrition? attint 0. No 1. Yes C21. Did the statistical analysis attempt to control for differential attrition effects? attstat 0. No 1. Yes 9. Don’t know/can’t tell C22. Statistical significance testing used? sigtest 0. No 1. Yes C23. Overall methodology rating methrat 1. Comparison group lacks demonstrated comparability to treatment group 2. Comparison between 2+ groups, one with and one without the intervention 3. Comparison between program group and one or more control groups, controlling for other factors, or nonequivalent comparison group is only slightly different from program group, or randomized controlled trial with high attrition 4. Random assignment and analysis <strong>of</strong> comparable program and comparison groups, including controls for attrition Notes on methodology: 187
D. SAMPLE LEVEL CODING SHEET Instructions: A study may report results separately for distinct samples (e.g., persons with/without prior arrests). Each distinct sample must have its own coding sheet. <strong>The</strong> treatment-comparison contrast is the same for the different samples. Samples should be independent; i.e., no overlapping participants. Some studies report the results broken down by different subgroups (e.g., by gender). Only one <strong>of</strong> these breakouts can be used – choose the one with the most information, or the one most relevant to the review. Identifying Information D1. Study ID: studid D2. Module ID: modid D3. Sample ID: sampid D4. Coder initials: cosamp Sample Description D5. Description <strong>of</strong> treatment group sample: txsamp D6. Description <strong>of</strong> comparison group sample: cxlsamp D7. Total N in treatment group at beginning <strong>of</strong> study: txn D8. Total N in comparison group at beginning <strong>of</strong> study: cxln Note: D7 + D8 = total sample size prior to attrition. If multiple samples are being coded, the sum across samples must equal the total sample size prior to attrition. D9. Age range <strong>of</strong> study participants: sampage 1. Adolescent (12-18) 5. Youth and adult 2. Youth (18-21) 6. Adolescent, youth, and adult 3. Adult (21+) 8. Other: 4. Adolescent and youth 9. Unspecified/can’t tell D10. Youngest age included in sample (999 if unknown): yage D11. Oldest age included in sample (999 if unknown): oage D12. Exact proportion <strong>of</strong> males in sample (if known): prmale D13. Approximate gender description <strong>of</strong> sample: sampgen 1. All male (>90%) 4. More females than males (60-90% 2. More males than females (60-90% female) male) 5. All female (>90%) 3. Roughly equal males and females 9. Can’t tell 188
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University of Penn
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In memory of Edwar
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Janel McCaffrey and Knakiya Hagans,
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traditional practice, we find no ev
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Methodology .......................
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LIST OF FIGURES Figure 1.1: Effect
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intensity makes no difference to re
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isk of committing
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impact of probatio
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which perhaps suggests that ISP is
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program intended to reduce the stra
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supervision with probation
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3. To what extent do the risk/need
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Methods Scale (SMS: Farrington et a
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Types of Outcomes
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Description of met
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actual behavior. We analyze technic
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Treatment of quali
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treatment group, and those to the r
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Discussion of Resu
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were evaluated in the same report (
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direction of effec
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To what extent does program philoso
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Which other components of</
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.450; technical violations: Q B < .
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it should be noted that those progr
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up in unpublished reports than thos
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violations first went before a judg
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2 One U.S. estimate indicates that
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Tables Table 1.1: Characteristics <
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Table 1.3: Moderator Variable <stro
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Table 1.4: Moderator Variable <stro
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Figures Figure 1.1: Effect
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Figure 1.5: Effect of</stro
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CHAPTER 2. ‘Low-Intensity
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What Works in Probation Supervision
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to do with it. Furthermore, the mor
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to the New York City and Oregon stu
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Barnes et al. (forthcoming) have su
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paradox.” He suggests that ‘not
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fatal shootings in Philadelphia are
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the proportions of
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Interventions and Follow-Up Probati
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officers more <str
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1. Does the effect of</stro
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all, resulting in a large number <s
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Differential treatment take-up and
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control group members who received
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effect of LIS on r
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incarcerated must also be removed f
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offenders in our s
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ecidivists in the sample, 77 commit
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(IRR = 1.41, p ≤ .107). SES did n
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probability of fai
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The count model ou
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estimate is also practically identi
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twice the risk of
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an end. On the other hand, research
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low-intensity supervision would imp
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Conclusion The aim
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We found that low-risk of</
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7 LIS participants who were transfe
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Tables Table 2.1: Sample Characteri
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Table 2.3: Frequency of</st
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Table 2.5: Instrumental Variables M
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Table 2.7: Prevalence of</s
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Table 2.9: Time to Failure (Violent
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Table 2.12: Treatment Effect by Sub
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Table 2.14: Frequency of</s
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Table 2.16: Instrumental Variables
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Figures Figure 2.1: Risk-Based Allo
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Figure 2.5: Survival Time for LIS E
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CHAPTER 3. Risk Prediction for Effe
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sensitivity of the
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Programs should be designed to adhe
Page 151 and 152: weight information in an appropriat
Page 153 and 154: statistical model that would predic
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Page 157 and 158: assignment pool. Backfill probation
Page 159 and 160: Little research has been done on th
Page 161 and 162: already predicted to be at low risk
Page 163 and 164: It assumes that if of</stro
Page 165 and 166: involved. Crimes that obviously met
Page 167 and 168: We examine the potential interactio
Page 169 and 170: age is based on this date regardles
Page 171 and 172: obberies. The only
Page 173 and 174: of low-intensity s
Page 175 and 176: classified as low risk. The
Page 177 and 178: All the risk ratios in Table 3.9 in
Page 179 and 180: 0.55. Raising the threshold results
Page 181 and 182: are partly selected on the basis <s
Page 183 and 184: make up the majority of</st
Page 185 and 186: strategy allows probation o
Page 187 and 188: Notes 1 In this study, murder, atte
Page 189 and 190: Table 3.2: Sample Characteristics (
Page 191 and 192: Table 3.6: Predictive Ability at Al
Page 193 and 194: Table 3.9: Post-Random Assignment O
Page 195 and 196: APPENDICES Appendix A: Systematic R
Page 197 and 198: combination. The s
Page 199 and 200: B. ELIGIBILITY CHECKLIST B1. First
Page 201: Other: txcxloth C6d. Additional pro
Page 205 and 206: E. DEPENDENT VARIABLE CODING SHEET
Page 207 and 208: F14. Comparison group sample size f
Page 209 and 210: weight w is then recalculated (6),
Page 211 and 212: Study Sheffield (Males) 1976 (Folka
Page 213 and 214: Study Dallas TX 1992 (Turner & Pete
Page 215 and 216: Study Minnesota ISR 1995 (Deschenes
Page 217 and 218: Study Clark WA 2003 (Barnoski, 2003
Page 219 and 220: Study Whatcom WA 2003 (Barnoski, 20
Page 221 and 222: Study Los Angeles CA 2005 (Zhang &
Page 223 and 224: Fed. Prob., 56, 12-17. Turner, Pete
Page 225 and 226: Study Reference Benekos & Sonnenber
Page 227 and 228: Study Reference Giblin (2002) Using
Page 229 and 230: Study Reference Lasater et al. (n.d
Page 231 and 232: Study Reference Robertson (2000) Co
Page 233 and 234: Study Reference Turner & Greene (19
Page 235 and 236: Appendix E: Philadelphia APPD Low-<
Page 237 and 238: Prevalence of Reci
Page 239 and 240: Frequency of Recid
Page 241 and 242: Instrumental Variables Model: Preva
Page 243 and 244: Instrumental Variables Model: Preva
Page 245 and 246: Post-RA Months in Jail and Probabil
Page 247 and 248: Scaled Schoenfeld Residuals Time =
Page 249 and 250: BIBLIOGRAPHY Chapter 1 ** Denotes t
Page 251 and 252: Cook, T. D., & Campbell, D. T. (197
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Glaze, L. E, & Bonczar, T. P. (2009
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MacKenzie, D. L. (2006a). What work
Page 257 and 258:
Petersilia, J., Turner, S., & Desch
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safety first: 13 strategies for suc
Page 261 and 262:
Wilson, D. B. (2010). Meta-analysis
Page 263 and 264:
Angrist, J. D. (2006). Instrumental
Page 265 and 266:
Clear, T. R., & Hardyman, P. L. (19
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period266.pdf Lowenkamp, C. T., Lat
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Rosch, J. (2006). Deviant peer cont
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Taxman, F. S., & Thanner, M. (2006)
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statistical learning. Journal <stro
Page 275 and 276:
Federal Bureau of
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Marsh, K., & Fox, C., (2008). <stro
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Sherman, L. W. (1993). Defiance, de
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