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，下降的速度已经放缓，甚至在2002年（最近一年的报告）出现逆转。此外，种族和民族差异也有所增加。因此，婴儿死亡率仍然是一个严重的公共卫生问题。此外，种族和民族差异的原因仍然难以捉摸。我们认为，有有效的理论工具，例如婴儿死亡率的近似决定因素模型，但没有充分实施这些模型的统计工具。理想情况下，这些工具应该适应直接和间接（通过近似决定因素）影响，允许非线性效应，适当地参数化近似决定因素（其中最重要的是出生体重和胎龄），并解释出生队列中“隐藏”的异质性。本申请的目的是继续发展协变量密度定义的逻辑回归（和其他glm）的混合物，这是一种可以操作近似决定因素模型的统计方法。我们之前工作的目的是验证统计模型，检查有关近似决定因素结构的一些问题，并证明模型在研究外生协变量方面的效用。我们将在这里扩展这些结果，以检验有关出生体重与婴儿死亡率的“因果关系”的具体假设，即，近似决定因素的“结构”如何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”一直受到质疑，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从统计上检验这些假设。我们将在种族多样化出生队列样本的近似决定因素模型的背景下检查一些潜在的协变量。我们将开发并提供进行协变量密度定义的GLMs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.