| 書(shū)目名稱(chēng) | Demystifying Causal Inference | | 副標(biāo)題 | Public Policy Applic | | 編輯 | Vikram Dayal,Anand Murugesan | | 視頻video | http://file.papertrans.cn/266/265456/265456.mp4 | | 概述 | Provides public policy applications.Contains careful explanation of R code in applications.Explains concepts using causal graphs and simulations | | 圖書(shū)封面 |  | | 描述 | This book provides an accessible introduction to causal inference and data analysis with R, specifically for a public policy audience. It aims to demystify these topics by presenting them through practical policy examples from a range of disciplines. It provides a hands-on approach to working with data in R using the popular tidyverse package. High quality R packages for speci?c causal inference techniques like ggdag, Matching, rdrobust, dosearch etc. are used in the book..The book is in two parts. The first part begins with a detailed narrative about John Snow’s heroic investigations into the cause of cholera. The chapters that follow cover basic elements of R, regression, and an introduction to causality using the potential outcomes framework and causal graphs. The second part covers specific causal inference methods, including experiments, matching, panel data, difference-in-differences, regression discontinuity design, instrumental variables and meta-analysis, with the help of empirical case studies of policy issues.?.The book adopts a layered approach that makes it accessible and intuitive, using helpful concepts, applications, simulation, and data graphs. Many public policy q | | 出版日期 | Textbook 2023 | | 關(guān)鍵詞 | Causal inference; R; Simulation; Regression; Regression Discontinuity; Panel Data; Public policy; impact ev | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-99-3905-3 | | isbn_softcover | 978-981-99-3907-7 | | isbn_ebook | 978-981-99-3905-3 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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