{"title":"洪光磊《社会世界中的因果关系》书评","authors":"K. Frank, G. Saw, Ran Xu","doi":"10.1353/obs.2016.0001","DOIUrl":null,"url":null,"abstract":"As the introduction of Guanglei Hong’s Causality in a Social World makes clear, this book would not be necessary if all treatments we wished to study had constant effects through simple mechanisms on independent individuals who were randomly assigned to treatments. While, such conditions may hold in some idealized agricultural settings, this is not the phenomenon we encounter in a social policy oriented world with human agency. In response, Hong presents a coherent theoretical and empirical framework for estimating causality when people choose their own treatments, when they encounter mediating and moderating effects of treatments and when they influence others’ choices and outcomes. The book is presented in four large sections: overview, moderation, mediation and spillover, with a chapter introducing the core ideas in each section (chapters 4, 7, 11 and 14 respectively). Beyond merely consolidating her own foundational work, the book is steeped in deep and historical statistical principles of sampling, propensity score analysis, mediation and moderation, and spill-over mechanisms. Ultimately, the book will mark a passageway from underlying statistical principles to a framework that may endure and expand beyond even what Hong anticipates.","PeriodicalId":74335,"journal":{"name":"Observational studies","volume":"2 1","pages":"86 - 89"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1353/obs.2016.0001","citationCount":"0","resultStr":"{\"title\":\"Book review of “Causality in a Social World” by Guanglei Hong\",\"authors\":\"K. Frank, G. Saw, Ran Xu\",\"doi\":\"10.1353/obs.2016.0001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the introduction of Guanglei Hong’s Causality in a Social World makes clear, this book would not be necessary if all treatments we wished to study had constant effects through simple mechanisms on independent individuals who were randomly assigned to treatments. While, such conditions may hold in some idealized agricultural settings, this is not the phenomenon we encounter in a social policy oriented world with human agency. In response, Hong presents a coherent theoretical and empirical framework for estimating causality when people choose their own treatments, when they encounter mediating and moderating effects of treatments and when they influence others’ choices and outcomes. The book is presented in four large sections: overview, moderation, mediation and spillover, with a chapter introducing the core ideas in each section (chapters 4, 7, 11 and 14 respectively). Beyond merely consolidating her own foundational work, the book is steeped in deep and historical statistical principles of sampling, propensity score analysis, mediation and moderation, and spill-over mechanisms. Ultimately, the book will mark a passageway from underlying statistical principles to a framework that may endure and expand beyond even what Hong anticipates.\",\"PeriodicalId\":74335,\"journal\":{\"name\":\"Observational studies\",\"volume\":\"2 1\",\"pages\":\"86 - 89\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1353/obs.2016.0001\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Observational studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1353/obs.2016.0001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Observational studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1353/obs.2016.0001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Book review of “Causality in a Social World” by Guanglei Hong
As the introduction of Guanglei Hong’s Causality in a Social World makes clear, this book would not be necessary if all treatments we wished to study had constant effects through simple mechanisms on independent individuals who were randomly assigned to treatments. While, such conditions may hold in some idealized agricultural settings, this is not the phenomenon we encounter in a social policy oriented world with human agency. In response, Hong presents a coherent theoretical and empirical framework for estimating causality when people choose their own treatments, when they encounter mediating and moderating effects of treatments and when they influence others’ choices and outcomes. The book is presented in four large sections: overview, moderation, mediation and spillover, with a chapter introducing the core ideas in each section (chapters 4, 7, 11 and 14 respectively). Beyond merely consolidating her own foundational work, the book is steeped in deep and historical statistical principles of sampling, propensity score analysis, mediation and moderation, and spill-over mechanisms. Ultimately, the book will mark a passageway from underlying statistical principles to a framework that may endure and expand beyond even what Hong anticipates.