【2015】Causal Inference for Statistics, Social, and Biomedical Sciences

非常感谢楼主提供好资料！

非常感谢！

当面对创新的事物时，如若受思维定势约束，就会形成对创造力的障碍。敢于突破，才有创造力。

在人大找到了这本居然 感谢

thank you very much

这本应该不错哟！！！！！！！！！！

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.

haoshu, xiexie LZ

thank you very much

太赞了！期待已久。