title: Modeling low birth weights using threshold regression: results for U.S. birth data.
abstract: Babies born live under 2,500 g or with a gestational age under 37 weeks are often inadequately developed and have elevated risks of infant mortality, congenital malformations, mental retardation, and other physical and neurological impairments. In this paper, we model birth weight as a first hitting time (FHT) of a birthing boundary in a Wiener process representing fetal development. We associate the parameters of the process and boundary with covariates describing maternal characteristics and the birthing environment using a relatively new regression methodology called threshold regression. Two FHT models for birth weight are developed. One is a mixture model and the other a competing risks model. These models are tested in a case demonstration using a 4%-systematic sample of the more than four million live births in the United States in 2002. An extensive data set for these births was provided by the National Center for Health Statistics. The focus of this paper is on the conceptual framework, models and methodology. A full empirical study is deferred to a later occasion.
authors.affiliation: Desautels Faculty of Management, McGill University, Montreal, QC, Canada H3A 1G5. george.whitmore@mcgill.ca
authors.forename: G A
authors.initials: GA
authors.lastname: Whitmore
authors.forename: Yi
authors.initials: Y
authors.lastname: Su
mesh_terms: D001499:Bayes Theorem; D006801:Humans; D007230:Infant, Low Birth Weight; D007231:Infant, Newborn; D047928:Premature Birth; D012044:Regression Analysis; D014481:United States / Q000453:epidemiology