Restrictive Housing Placement and Length of Stay: A Latent Class Analysis With Mixed Distributions

Abstract

On average, one in five incarcerated persons will spend some time in restrictive housing (RH) during their incarceration. Despite a growing body of research on the topic of RH, few have taken into account the heterogeneity of the incarcerated individuals’ pre-RH risk profiles. In the present study, we fill this gap by estimating a latent class analysis (LCA) model to explore the heterogeneity among a sample of incarcerated individuals in New Jersey. Our LCA has both dichotomous and count variables, and we specified a model with logit and Poisson functional forms. We then examine how the latent group membership predicted RH placement and length of stay using a hurdle model. We identified a four-group LCA model, and found that groups featuring misconduct records were more likely to experience RH and stay longer in RH. Prior criminal records were less predictive of these RH outcomes.