Differential treatment in the youth justice system - Equality and ...
Differential treatment in the youth justice system - Equality and ...
Differential treatment in the youth justice system - Equality and ...
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Appendix D:Multivariate logistic regressionAPPENDICESThe follow<strong>in</strong>g tables present <strong>the</strong> results of regression analysis that tested whe<strong>the</strong>r <strong>the</strong>reare differences <strong>in</strong> outcomes for young people of different ethnic groups controll<strong>in</strong>g for arange of case characteristics. The model is based on a complete year (2006) of youngpeople who have been charged with an offence. This means that a young person canappear <strong>in</strong> <strong>the</strong> dataset more than once, <strong>and</strong> that <strong>in</strong>dividual cases were not <strong>in</strong>dependentof each o<strong>the</strong>r. This violates an assumption for logistic regression which often leads tounderestimated st<strong>and</strong>ard errors.To adjust for <strong>the</strong> dependent data, <strong>the</strong> statistical package STATA logistic regression withr<strong>and</strong>om effect was used, <strong>and</strong> <strong>the</strong> <strong>in</strong>tra-class correlation (which is produced as part of <strong>the</strong>model) was exam<strong>in</strong>ed to see what proportion of <strong>the</strong> variance was expla<strong>in</strong>ed by <strong>the</strong>repeated occurrence of <strong>the</strong> <strong>in</strong>dividual only. If this proportion was not significantly differentto zero, <strong>the</strong>n it can be assumed that case characteristics have expla<strong>in</strong>ed away all<strong>in</strong>dividual effects <strong>and</strong> that results are similar to a logistic regression without controll<strong>in</strong>g for<strong>the</strong> repeated occurrence (produced us<strong>in</strong>g <strong>the</strong> statistical package SPSS). The Hausmantest was conducted on <strong>the</strong> logistic r<strong>and</strong>om effect model to test whe<strong>the</strong>r <strong>the</strong> model wasconsistent. In cases where <strong>the</strong> r<strong>and</strong>om effect model was shown to be <strong>in</strong>consistent, but <strong>the</strong><strong>in</strong>traclass correlation <strong>in</strong>dicated that a proportion of <strong>the</strong> variance was expla<strong>in</strong>ed by <strong>the</strong><strong>in</strong>dividual, <strong>the</strong>n a logistic regression was run with clustered robust st<strong>and</strong>ard errors.Pre-court decisionsTo model pre-court decisions, we needed to identify all those young people who wereavailable for a pre-court disposal. We selected all young people who had scored less thanthree on <strong>the</strong> variable count<strong>in</strong>g <strong>the</strong> number of previous convictions, provided that <strong>the</strong>y hadpleaded guilty to <strong>the</strong> current offence. 61,62 This resulted <strong>in</strong> a sample of 5,325 boys <strong>and</strong>1,931 girls. The sub-sample did not precisely identify all those who received a pre-courtdisposal, identify<strong>in</strong>g 87% <strong>and</strong> 89% of reprim<strong>and</strong>s of boys <strong>and</strong> girls, <strong>and</strong> 76% <strong>and</strong> 78%of f<strong>in</strong>al warn<strong>in</strong>g for boys <strong>and</strong> girls. The variable ‘no previous convictions’ may provideunderestimates of young people with no previous convictions. For all cases <strong>in</strong>volv<strong>in</strong>gboys, 15% had no previous convictions, which is smaller than <strong>the</strong> 54.8% found by Feilzer6162The ‘guilty plea’ variable <strong>in</strong>cludes admissions of guilt made at police stations.We are aware that offenders with two previous convictions are <strong>in</strong>eligible for pre-court disposals, butour database shows that many such offenders received f<strong>in</strong>al warn<strong>in</strong>gs. We were unable to establishwhe<strong>the</strong>r <strong>the</strong> variable actually counts <strong>the</strong> number of contacts with <strong>the</strong> police <strong>and</strong> <strong>youth</strong> <strong>justice</strong> <strong>system</strong><strong>in</strong>clud<strong>in</strong>g <strong>the</strong> present contact – which would make sense of <strong>the</strong> pattern of f<strong>in</strong>d<strong>in</strong>gs that we haveseen.124