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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.

在多元正态分布假设下，发展了用于复杂因果关系分析的图形建模技术。因此，它们仅限于线性因果关系建模。'lb消除了这个限制，我们在这个项目中开发了基于秩相关矩阵的图形建模技术。该方法被用于研究环境污染物的联合风险，如二恶英，多氯联苯和农药，测量120名妇女母乳中这些化学物质的含量，并测量这些母亲的婴儿的甲状腺和免疫激素状态。结果发现甲状腺功能与二恶英的比值比为1.65（p=0.29），但为7.15（p=0.02），进一步发展了一种基于潜在结构模型的图形建模技术，探索了处理时间序列数据的方法，并对上述方法进行了理论研究;即（i）通过分层调整混杂变量，制定了比较两个负二项分布的估计和检验方法。㈡制定了一种非参数估算方法。(iii)开发了一种理论，通过使用各种基函数对数据进行建模来从高维数据中提取信息;开发了一种贝叶斯信息标准来选择模型;不仅将其应用于图形建模，而且还将其应用于其他统计方法，如DNA数据的差异分析等。（四）发展了一种在一比K多重比较情况下对重复测量数据进行图形建模的理论，并为所涉参数制定了一个近似置信区间。（v）建立了小扩散过程的未知漂移参数和扩散参数的估计理论，证明了它们的相合性和渐近正态性。