Development and Application of Graphical Modeling techniques for Assesshrg the Joint Risks of Contaminants

评估污染物联合风险的图形建模技术的开发和应用

基本信息

批准号：
15300093
负责人：
YANAGAWA Takashi
金额：
$ 4.61万
依托单位：
Kurume University (2004)Kyushu University (2003)
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2004
项目状态：
已结题

项目摘要

The graphical modeling techniques which have been proposed for the analysis of complex causal relationship are developed under the assumption of multivariate normal distribution. Thus they are limited for modeling only linear cause-effect relationships. 'lb remove this restriction we developed in this project graphical modeling techniques based on rank correlation matrix. The method was applied for studying joint risks of environmental contaminants such as Dioxin, PCB and pesticides measuring the amount of these chemicals in breast milks of 120 women and also measuring the thyroid and immune hormone status of infants from those mothers. It was discovered by the method that the odds ratios of thyroid function and Dioxin was 1.65 (p=0.29), but was 7.15 (p=0.02) when adjusted for PCB.We further developed a method of graphical modeling technique that used latent structure models, and also explored the method that may deal with time series data.Theoretical studies were conducted to develop those methods mentioned above ; namely(i)Developed estimation and testing method for comparing two negative binomial distributions by adjusting for confounding variables by stratification.(ii)Developed a method of nonparametric imputation.(iii) Developed a theory to extract information from high dimensional data by modeling the data using various base functions ; developed a Bayes Information criteria to select the models; applied it to not only the graphical modeling but also other statistical methods such as disiminant analysis for DNA data and others.(iv)Developed a theory of graphical modeling for repeated measurements data in one to K multiple comparison setting and developed an approximate confidence intervals for the parameters involved.(v)Developed theory for estimating unknown drift parameter and diffusion parameter of the diffusion process with small diffusion and proved their consisitency and asymptotic normality.

在多元正态分布的假设下，开发了用于分析复杂因果关系的图形建模技术。因此，它们仅用于建模线性因果关系。 'lb删除了我们基于等级相关矩阵的项目图形建模技术中开发的这种限制。该方法用于研究环境污染物的关节风险，例如二恶英，PCB和农药，测量了120名妇女乳房中这些化学物质的数量，并测量了这些母亲的甲状腺和免疫激素状态。通过方法发现，甲状腺功能和二恶英的优势比为1.65（p = 0.29），但在对PCB进行调整时为7.15（p = 0.02）。我们进一步开发了一种图形建模技术，该方法使用潜在的结构模型，并探索了可能与时间序列数据相关的方法。在上面提到了这些方法。即（i）开发了通过分层调整混杂变量来比较两个负二项式分布的估计和测试方法。（ii）开发了一种非参数插补的方法。（iii）开发了一种理论，通过使用各种基本功能对数据进行建模，从而从高维数据中提取信息；开发了贝叶斯信息标准以选择模型；不仅将其应用于图形建模，还将其应用于其他统计方法，例如对DNA数据和其他数据的不限制分析。（iv）开发了一种用于重复测量数据的图形模型理论，用于k多重比较设置，并开发了涉及的参数的近似置信区间。正常。