A Bayesian Analysis of the Colorado Springs Spouse Abuse Experiment

This Article analyzes data from the Colorado Springs Spouse Abuse Experiment. In that experiment, suspects apprehended for misdemeanor spouse abuse were assigned at random to one of four treatments: (1) an emergency order of protection for the victim coupled with arrest of the suspect; (2) an emerge... Full description

This Article analyzes data from the Colorado Springs Spouse Abuse Experiment. In that experiment, suspects apprehended for misdemeanor spouse abuse were assigned at random to one of four treatments: (1) an emergency order of protection for the victim coupled with arrest of the suspect; (2) an emergency order of protection for the victim coupled with immediate crisis counseling for the suspect; (3) an emergency order of protection only; or (4) restoring order at the scene with no emergency order of protection. Outcome measures are taken from official police data and from follow-up interviews with victims. Using Bayesian procedures to take previous experiments into account, the balance of evidence supports a deterrent effect for arrest among "good risk" offenders, who presumably have a lot to lose by being arrested. The balance of evidence is far more equivocal for a "labeling effect" in which an arrest increases the likelihood of new violence.