The Effects of Sanction Intensity on Criminal Conduct - JDAI Helpdesk

Notes
1 In this study, murder, attempted murder, aggravated assault, robbery, and sexual <strong>of</strong>fenses were deemed
‘serious’ <strong>of</strong>fenses.
2 Intake information includes the <strong>of</strong>fender’s personal and residential characteristics, and information about
the instant <strong>of</strong>fense and prior criminal history.
3 Full details about the experimental design and how the sample was selected, assessed for eligibility, and
randomly assigned may be found in Barnes et al. (forthcoming).
4 An alternative approach could be to use incarceration status as a proxy for cost. <strong>The</strong> disadvantage is that
we must use either actual incarceration data for our sample, or assume the types <strong>of</strong> <strong>of</strong>fenses that might
result in a sentence <strong>of</strong> imprisonment. Assumptions may be too subjective given the discretion involved in
sentencing (although state sentencing guidelines could assist), and full incarceration data are not available
for our sample. In particular, it is possible that some post-random assignment sentencing decisions are still
pending given the relatively short period <strong>of</strong> time since the experiment ended. While assigning victim status
to each <strong>of</strong>fense type also involves assumptions, the level <strong>of</strong> subjectivity is likely considerably lower than it
would be for incarceration.
5 Most <strong>of</strong>fenses in the dataset are derived from the Pennsylvania Consolidated Statutes, Section 18 (Crimes
and Offenses).
6 <strong>The</strong> risk ratio is simply pE=1 /p E=0 (where p = probability and E = dichotomous exposure status), whereas
the odds ratio is (p/(1-p) E=1 )/(p/(1-p) E=0 ). <strong>The</strong> odds ratio tends to overstate our ‘natural’ interpretation <strong>of</strong>
relative outcomes: if the exposed group has a 50% risk <strong>of</strong> disease and the unexposed group has a 25% risk,
the risk ratio is clearly 2 (the exposed group is twice as likely to get the disease than the unexposed group),
but the odds ratio is 3 (the odds <strong>of</strong> disease in the exposed group are three times those <strong>of</strong> disease in the
unexposed group), which seems greater. <strong>The</strong> risk ratio also remains stable regardless <strong>of</strong> the size <strong>of</strong> the risk;
the magnitude <strong>of</strong> the odds ratio is closer to the risk ratio when the probability <strong>of</strong> disease in each group is
small, and further away when it is large. Following the example above, if the risks were reduced to 20%
and 10% respectively, the risk ratio would still be 2 but the odds ratio would fall to 2.25.
7 In addition, an adjusted risk ratio that is substantially different from the unadjusted risk ratio (a 10-15%
difference is a commonly-used rule <strong>of</strong> thumb) suggests that the stratifying variable is a confounder.
8 <strong>The</strong> race indicator variable was populated with data from two different sources, with one source selected
as the default. However, serious discrepancies arose because the categories <strong>of</strong> race in the two original
sources were substantially different.
9 On the other hand, it is also possible that non-low risk probationers are in fact more serious <strong>of</strong>fenders, and
are more likely to be incarcerated as a result.
10 That past behavior is one <strong>of</strong> the strongest predictors <strong>of</strong> future behavior is one <strong>of</strong> the best documented
findings in criminological research (e.g., Nagin & Paternoster, 1991; Nagin & Farrington, 1992).
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