Meta regression analysis framework: the effectiveness of correctional education in

reducing recidivism

Margaret Giles, PhD

Paper presented to MAER-Net Colloquium, University of Athens, Greece, 12 September 2014

Take home message

• Question 1: What study characteristics are driving the difference between effect sizes in studies of the effectiveness of correctional education?

• Question 2: How is the effectiveness of correctional education measured?– Recidivism (Davis et al 2013)– Post release employment (Davis et al 2013)– Post release welfare dependence (Giles and Whale

2014)

Studies of effectiveness of correctional education on recidivism

• Many• Most show positive effects or NPV > 0• Study in prison reduces the propensity to offend

– Increases the opportunity cost of crime– Reduces impatience/time discount rates so more risk averse

• Irrespective of how recidivism is defined– Re-offending– More charges– More and/or longer consecutive custodial sentences– Sentences for more serious offences– Shorter time in the community between consecutive prison terms

Re-incarceration

• Time– Within one year– Within two years– Within the limit of the data– Within seven years– Within four years – Within n or N+ years

• Offence– Only counted if it is a new offence– Counted for new offence and/or breach of parole or other

breaches in relation to previous offence (whatever reason)

Types of data

• Justice system data (total offending history)– Same name?– Are previous records good enough?

• Prison data• Sample data• Prison AND employment data (Nally et al.

2012)• Matched data (UK Ministry of Justice 2010)

Data and methodology

Davis et al 2013 systematic review of 50 studies of the effectiveness of correctional education• Concluded that correctional education does

reduce recidivism and is cost effective.• Only US studies• 1 January 1980 to 31 December 2011• Recidivism, employment and achievement test

scores

Figure 1: Frequency distribution of studies by publication date (Davis et al. 2013)

1975 1980 1985 1990 1995 2000 2005 2010 20150

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Figure 2: Distribution of odds ratios for effect size estimates (Davis et al. 2013)

0 5 10 15 20 25 30 35 40 45 500

0.2

0.4

0.6

0.8

1

1.2

1.4

Where to from here?

• Co-researcher - Dr James Fogarty, The University of Western Australia (Stanley et al. 2013 Guidelines for MRA)

• MRA on 50 studies• MRA on 50+ studies– Outside the US (international)– After 31 December 2011 (more recent)