{"title":"因果推断:关键发展、过去和未来","authors":"Erica E. M. Moodie, David A. Stephens","doi":"10.1002/cjs.11718","DOIUrl":null,"url":null,"abstract":"<p>Causality is a subject of philosophical debate and a central scientific issue with a long history. In the statistical domain, the study of cause and effect based on the notion of “fairness” in comparisons dates back several hundreds of years, yet statistical concepts and developments that form the area of causal inference are only decades old. In this article, we review the core tenets and methods of causal inference and key developments in the history of the field. We highlight connections with traditional “associational” statistical methods, including estimating equations and semiparametric theory, and point to current topics of active research in this crucial area of our field.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11718","citationCount":"1","resultStr":"{\"title\":\"Causal inference: Critical developments, past and future\",\"authors\":\"Erica E. M. Moodie, David A. Stephens\",\"doi\":\"10.1002/cjs.11718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Causality is a subject of philosophical debate and a central scientific issue with a long history. In the statistical domain, the study of cause and effect based on the notion of “fairness” in comparisons dates back several hundreds of years, yet statistical concepts and developments that form the area of causal inference are only decades old. In this article, we review the core tenets and methods of causal inference and key developments in the history of the field. We highlight connections with traditional “associational” statistical methods, including estimating equations and semiparametric theory, and point to current topics of active research in this crucial area of our field.</p>\",\"PeriodicalId\":55281,\"journal\":{\"name\":\"Canadian Journal of Statistics-Revue Canadienne De Statistique\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11718\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Canadian Journal of Statistics-Revue Canadienne De Statistique\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cjs.11718\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Statistics-Revue Canadienne De Statistique","FirstCategoryId":"100","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cjs.11718","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Causal inference: Critical developments, past and future
Causality is a subject of philosophical debate and a central scientific issue with a long history. In the statistical domain, the study of cause and effect based on the notion of “fairness” in comparisons dates back several hundreds of years, yet statistical concepts and developments that form the area of causal inference are only decades old. In this article, we review the core tenets and methods of causal inference and key developments in the history of the field. We highlight connections with traditional “associational” statistical methods, including estimating equations and semiparametric theory, and point to current topics of active research in this crucial area of our field.
期刊介绍:
The Canadian Journal of Statistics is the official journal of the Statistical Society of Canada. It has a reputation internationally as an excellent journal. The editorial board is comprised of statistical scientists with applied, computational, methodological, theoretical and probabilistic interests. Their role is to ensure that the journal continues to provide an international forum for the discipline of Statistics.
The journal seeks papers making broad points of interest to many readers, whereas papers making important points of more specific interest are better placed in more specialized journals. The levels of innovation and impact are key in the evaluation of submitted manuscripts.