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使用阈值回归对低出生体重进行建模:美国出生数据的结果

Modeling low birth weights using threshold regression: results for U.S. birth data.

作者信息

Whitmore G A, Su Yi

机构信息

Desautels Faculty of Management, McGill University, Montreal, QC, Canada H3A 1G5.

出版信息

Lifetime Data Anal. 2007 Jun;13(2):161-90. doi: 10.1007/s10985-006-9032-y. Epub 2007 Feb 8.

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.

摘要

出生时体重不足2500克或孕周不足37周的活产婴儿往往发育不全,婴儿死亡、先天性畸形、智力迟钝以及其他身体和神经损伤的风险较高。在本文中,我们将出生体重建模为代表胎儿发育的维纳过程中分娩边界的首次击中时间(FHT)。我们使用一种相对较新的回归方法——阈值回归,将该过程和边界的参数与描述母亲特征和分娩环境的协变量相关联。开发了两个出生体重的FHT模型。一个是混合模型,另一个是竞争风险模型。这些模型在一个案例演示中进行了测试,该演示使用了2002年美国400多万例活产中的4%系统样本。国家卫生统计中心提供了这些出生情况的广泛数据集。本文的重点是概念框架、模型和方法。全面的实证研究将留待以后进行。

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