Causal Inference for Statistics, Social, and Biomedical Sciences pdf epub mobi txt 电子书 下载 2025
- 计量经济学
- 统计
- Statistics
- Econometrics
- 科学研究
- 方法论
- Methodology
- 经济理论
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including, matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.
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勉强看完了一遍，准备二刷
评分Causal inference beyond Regressions. But still based on the Potential Outcome Framework.
评分案头参考书。内容过于偏向作者本人的研究，等在这个圈子里混久了就会知道这远非Causal Inference全貌。
评分偏啰嗦
评分Potential outcomes approach to causality
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