1998 Fiscal Year Final Research Report Summary
Study of Causal Analysis of Categorical Variables based Information Theory
| Project/Area Number |
09680313
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | OITA MEDICAL UNIVERSITY |
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Principal Investigator |
ESHIMA Nobuoki OITA MEDICAL UNIVERSITY Faculty of Medicine, Professor, 医学部, 教授 (20203630)
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| Project Period (FY) |
1997 – 1998
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| Keywords | Categorical variable / Causal analysis / Causal effect / Genelarized linear model / Information theory / Odds / Path analysis / Path coefficient |
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| Research Abstract |
In this study, causal analysis of categorical variables by using logit, loglinear, and generalized linear models was studied. The usual method for path analysis is based on linear regression models, and LISREL model is widely applied to many scientific fields, e.g. psychology, economics, social science, etc. On the other hand, in path analysis of categorical variables linear relationships among the variables cannot be assumed, and it is a difficulty question how the causal effects are assessed. In the first year, path analyisis based on logit models was studied. The causal effects, i.e. direct and indirect effects, were defined through baseline log odds ratio, and the path coefficient to be assigned to each path was defined by Kullaback-Leibler information that describes the distance between an employed model and the model that explanatory variables and response variables are independent. The results are reported in the paper :
Path analysis of categorical variables based on logit models,
and the above paper is submitted for publication. In the final year, path analysis based on loglinear and generalized linear models was considered by developing the results in the first year of this research. Causal effects of explanatory variables were discussed in both empirical and observational studies. I am getting the research completed as the paper :
Effect analysis in generalized linear models.
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