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Between ICA and SEM

ICA 和 SEM 之间

基本信息

批准号：
15500185
负责人：
KANO Yutaka
金额：
$ 2.37万
依托单位：
Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2005
项目状态：
已结题

项目摘要

(1) We have successfully introduced the ICA methodology of confirmatory nature and developed a new estimation method. These and related results were presented in IMPS2003 in Italy and in the annual meeting of the Behaviormetric Society of Japan in 2003.(2) We have proposed a new framework of Nonnormal SEM and applied it to the problem of statistical causal modeling. These and related results were presented in AIC30 in Yokohama and in the annual meeting of the Behaviormetric Society of Japan in 2003.(3) We organized an invited paper session entitled "Nonnormal Structural Equation Modeling" in IMPS2004 in California I myself chaired the session and gave a talk about "Between ICA and SEM."(4) We hosted an international symposium on ICA and SEM at the Nakanoshima Center in October in 2004. We had more than 80 participants.(5) We have studied specific structures on the mixing matrix in ICA in the analysis of risk and protective factors in criminal psychology.(6) In July of 2005, I gave an invited paper entitled "SEM and nonnormality" in the Netherlands in IMPS2005.(7) Using nonnormal information on data, we proposed a solution to the intrinsic problems of normal SEM such as no identifiable models, equivalent models, and saturate models.(8) We suggested to determine causal ordering of several nodes (observable variables) on the basis of ICA and path analysis of SEM.

(1)我们成功地引入了验证性的ICA方法，并开发了一种新的估计方法。这些结果和相关结果发表在2003年意大利的IMPS2003和2003年的日本行为测量学会年会上。(2)我们提出了一个新的非正态结构模型框架，并将其应用于统计因果建模问题。这些和相关的结果在横滨的AIC30和2003年的日本行为测量学会年会上公布。(3)我们在加利福尼亚组织了一次题为《IMPS 2004中的非正态结构方程建模》的特邀论文会议。我本人主持了会议，并就“ICA和扫描电子显微镜之间”发表了演讲。(4)我们于2004年10月在中野岛中心主办了一次关于ICA和扫描电子显微镜的国际研讨会。(5)研究了ICA中混合矩阵在犯罪心理学风险和保护因素分析中的具体结构。(6)2005年7月，我在IMPS2005上发表了一篇题为《结构方程与非正态分布》的特邀论文。(7)利用数据上的非正态信息，我们提出了解决正常结构方程的内在问题的方法，如没有可识别的模型、等价模型和饱和模型。(8)我们建议在独立成分分析和结构方程的通径分析的基础上，确定几个节点(可观测变量)的因果顺序。