Predictors of placement stability at the state level: the use of logistic regression to inform practice

Placement instability is often associated with a number of negative outcomes for children. To gain state level contextual knowledge of factors associated with placement stability/ instability, logistic regression was applied to selected variables from the New Mexico Adoption and Foster Care Administrative Reporting System dataset. Predictors identified in the model are consistent with previous research, reliable across time periods, and informative to the understanding of potential risk/protective factors of placement stability/instability specific to the New Mexico child welfare agency.