Predicting trips to health care facilities: A binary logit and receiver operating characteristics (ROC) approach

Abstract

This paper discusses an overarching framework that integrates latent variable models and prediction success with receiver operator characteristics (ROC) curves. In three illustrative examples that focus on trip purpose, health market indicators, and resources, the paper employs binary logit models and ROC methodology to identify factors that best discriminate individuals' trips to out-patient health care facilities. Data for the examples are a three-year longitudinal survey of persons 45 years and older in China. The study contributes to the sparse empirical economics literature using ROC methodologies and more broadly to the transportation and health literatures. The ROC applications provide new insights on health care trips, finding that out-patient trips for treatment, paying out-of-pocket costs, and lack of monetary resources are salient discriminators in one's trip choice decisions.