STATISTICAL METHODS FOR A MIXTURE OF SUBPOPULATIONS

这项研究将考察评估的内在困难。 当观测值的同一性为 还不完全清楚。硬聚类和模糊聚类技术 将观测数据分成子组的方法进行了研究。本研究 将制定亚群体的估计方法 特点。新方法的统计特性 将会被研究。新的方法论将与 旨在纠正错误分类问题的现有方法。 新的方法论将缓解一些内在的困难 对于不同亚群的混合。将会提出申请 关于生物异质性及其测量问题的研究 出生体重、胎龄和围产儿死亡率的误差。这 这项研究也将应用于胎儿宫内发育的研究。 以及妊娠结局。

This study will examine the intrinsic difficulty of estimating subpopulation characteristics when the identities of the observations are not completely known. Hard clustering and fuzzy clustering techniques to classify observations into subgroups are investigated. This study will develop estimation methodologies for the subpopulation characteristics. The statistical properties of the new methodologies will be studied. The new methodologies will be compared with the existing methodologies designed to remedy the misclassification problem. The new methodologies will alleviate some of the intrinsic difficulties for a heterogeneous mixture of subpopulations. Applications will be made to study the issues concerning biological heterogeneity and measurement error in the birth weight, gestational age and perinatal mortality. This study will also be applied to the investigation of intrauterine growth and pregnancy outcome.