The Determinants of Infant Mortality: Statistical Models

描述（由申请人提供）：从历史上看，美国婴儿死亡的总体风险已经下降。然而，在2002年，即报告的最近一年，下降速度有所减缓，甚至出现逆转。此外，种族和族裔差异也有所增加。因此，婴儿死亡率仍然是一个严重的公共卫生问题。此外，种族和族裔差异的原因仍然难以捉摸。我们认为，有效的理论工具，例如婴儿死亡率的直接决定因素模型是存在的，但使这些模型充分运作的统计工具却不存在。理想情况下，这些工具应适应直接和间接（通过直接决定因素）的影响，允许非线性效应，适当参数化的直接决定因素（其中最重要的是出生体重和胎龄），并考虑到“隐藏”的异质性在出生队列。这个应用程序的目的是继续发展协变量密度定义的混合逻辑回归（和其他GLM）的统计方法，可以操作的近似决定因素模型。我们以前的工作的目的是验证统计模型，研究一些问题的结构的直接决定因素的组成部分，并证明了效用的模型研究外生协变量。我们将在这里扩展这些结果，以测试有关出生体重与婴儿死亡率的“因果”滚动的具体假设，即如何“结构”的直接决定因素与外生协变量和婴儿死亡率相互作用。出生体重的“因果”关系受到质疑，这是设计干预措施的一个极端重要的问题。我们开发的方法能够在统计上检验这些假设。我们将研究一些潜在的协变量的背景下，在近因决定因素模型的样本种族多样化的出生队列。我们将开发并提供用于进行协变量密度定义的GLM混合物的程序。

DESCRIPTION (provided by applicant): Historically, the overall risk of infant mortality in the United States has declined. However, the rate of decline has slowed and even reversed in 2002 the most recent year reported. Further, racial and ethnic disparities have increased. Consequently, infant mortality remains a serious public health problem. Moreover, the cause of the racial and ethnic differentials has remained elusive. It is our view that effective theoretical tools, e.g. the proximate determinants model of infant mortality, are available, but that the statistical tools to fully operationalize these models are not. Ideally, these tools should accommodate direct and indirect (through the proximate determinants) effects, allow for non-linear effects, appropriately parameterize the proximate determinants (the most important of which are birth weight and gestational age), and account for "hidden" heterogeneity in the birth cohort. The objective of this application is to continue development of Covariate Density Defined mixtures of logistic regression (and other GLMs) a statistical methodology that can operationalize the proximate determinants model. The objective of our previous work was to validate the statistical model, examine a number of issues concerning the structure of the proximate determinants component, and demonstrate the utility of the model for studying exogenous covariates. We will extend these results here to test specific assumptions concerning the "causal" roll of birthweight with respect to infant mortality, i.e. how the "structure" of the proximate determinants interacts with exogenous covariates and infant mortality. The "causal" roll of birth weight has been questioned, an issue of extreme importance for designing interventions. The method we have developed is capable of statistically testing these assumptions. We will examine a number of potential covariates in the context of the proximate determinants model on a sample of ethnically diverse birth cohorts. We will develop and make available programs for conducting Covariate Density Defined mixtures of GLMs.