{"title":"利用多视点合并联合运算集成结构方程建模路径模型","authors":"R. Saga, Rikuto Kunimoto","doi":"10.1109/ISCBI.2013.48","DOIUrl":null,"url":null,"abstract":"This study describes a method for integration of multiple path models. Structural equation modeling (SEM) is useful for causality analysis. However, the result of SEM may lack reliability owing to the model being constructed upon subjective assumptions. To mitigate this condition, the integration of multiple path models by use of the union operation is proposed. Four integrations are performed in an experiment for each feature case and the method usability is discussed.","PeriodicalId":311471,"journal":{"name":"2013 International Symposium on Computational and Business Intelligence","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integration of Path Models for Structural Equation Modeling by Use of Union Operation for Merging Multiple Viewpoints\",\"authors\":\"R. Saga, Rikuto Kunimoto\",\"doi\":\"10.1109/ISCBI.2013.48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study describes a method for integration of multiple path models. Structural equation modeling (SEM) is useful for causality analysis. However, the result of SEM may lack reliability owing to the model being constructed upon subjective assumptions. To mitigate this condition, the integration of multiple path models by use of the union operation is proposed. Four integrations are performed in an experiment for each feature case and the method usability is discussed.\",\"PeriodicalId\":311471,\"journal\":{\"name\":\"2013 International Symposium on Computational and Business Intelligence\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Symposium on Computational and Business Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCBI.2013.48\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Symposium on Computational and Business Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCBI.2013.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integration of Path Models for Structural Equation Modeling by Use of Union Operation for Merging Multiple Viewpoints
This study describes a method for integration of multiple path models. Structural equation modeling (SEM) is useful for causality analysis. However, the result of SEM may lack reliability owing to the model being constructed upon subjective assumptions. To mitigate this condition, the integration of multiple path models by use of the union operation is proposed. Four integrations are performed in an experiment for each feature case and the method usability is discussed.