This study examines the relationship between houselessness and recidivism among people on probation with and without behavioral health problems. The study also illustrates a new way to summarize the effect of an exposure on an outcome, the Incremental Propensity Score (IPS), which avoids pitfalls of other estimation approaches commonly used in criminology. We assessed the impact of houselessness at probation start on rearrest within one year among a cohort of people on probation (n = 2,453). We estimated IPS effects, considering general and crime-specific recidivism if subjects were more or less likely to be unhoused and assessed effect variation by psychiatric disorder status. We used a doubly robust machine learning estimator to flexibly but efficiently estimate effects. Decreasing houselessness led to a lower estimated average rate of recidivism. Dividing the odds of houselessness by ten had a significant effect when compared to multiplying the odds of houselessness by ten, corresponding to a 9% reduction in the estimated average rate of recidivism (p < 0.05). Milder interventions showed smaller, non-significant effect sizes. Stratifying by diagnoses and re-arrest type led to similar results without statistical significance. Minding limitations related to observational data and generalizability, this study supports houselessness as a risk factor for recidivism across populations with a new analytic approach. Efforts to reduce recidivism should include interventions that make houselessness less likely, such as increasing housing access. Meanwhile, efforts to establish recidivism risk factors should consider alternative effects like IPS effects to maximize validity and reduce bias.

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