書誌事項
- タイトル別名
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- On the Structural Causal Model
- コウゾウテキ インガ モデル ニ ツイテ
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説明
This paper reviews basic ideas of Structural Causal Models (SCMs) proposed by Judea Pearl (1995, 2009a). SCMs are nonparametric structual equation models which express cause-effect relationship between variables, and justify matematical principles of both the potential outcome approach and the graphical model approach for statistical causal inference. In this paper, considering the difference/connection between SCMs and Rubin's Causal Models (RCMs) (Rubin, 1974, 1978, 2006), we state that (1) the expressive power of the potential outcome approach is higher than that of the graphical model approach, but (2) the graphical model approach. From these consderations, we conclude that we should discuss statistical causal inference based on both approaches.
収録刊行物
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- 計量生物学
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計量生物学 32 (2), 119-144, 2012
日本計量生物学会
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詳細情報 詳細情報について
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- CRID
- 1390282679345805184
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- NII論文ID
- 10030631609
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- NII書誌ID
- AA11591618
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- ISSN
- 21856494
- 09184430
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- NDL書誌ID
- 023796850
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- 本文言語コード
- ja
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- 資料種別
- journal article
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- データソース種別
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- JaLC
- NDLサーチ
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可
