因果推論
Causal Inference
| 節 | 週一 |
|---|---|
2 09:00–09:50 | 因果推論 A406 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
This course (IST5556: causal inference and mediation analysis) introduce methods for causal inference, mediation analysis and interaction analysis. The course begins with presenting four steps widely used in causal theory development: (1) Counterfactual (potential) outcome model, (2) Direct Acyclic Graphs, (3) Identification, and (4) Estimation; and then explored in specific topics such as time-varying system, mediation analysis, alternative definitions in mediation analysis, and different methods for estimation. Students who take this course are expected to be equipped with sufficient techniques to develop causal theory in a certain topic and conduct data analysis based on causal model.
No prerequisites for this course, but familiarity with basic statistical inference and regression model will be assumed. Some exposure to data analysis with statistics software (especially R) will be helpful.
Final: 20% Homework: 60% Report: 5%+5%+10% Bonus: 5%
| 週次 | 主題 |
|---|---|
| 第 1 週 | 課程大綱介紹、分組 |
| 第 2 週 | 課程:因果經濟學導讀 作業:Hw0 |
| 第 3 週 | 課程:小組報告、必備知識1-6 作業:簡報檔 |
| 第 4 週 | 課程:因果推論1-5 作業:Hw1 |
| 第 5 週 | 國慶連假 |
| 第 6 週 | 課程:因果推論6-12 |
| 第 7 週 | 課程:因果推論架構與概念1-12 |
| 第 8 週 | 課程:Data analysis DEMO 作業:Hw2 |
| 第 9 週 | 課程:NDE and NIE 1~7 |
| 第 10 週 | 課程:NDE and NIE 8~14 作業:期中作業 |
| 第 11 週 | 課程:Binary outcome 1~4 作業:Hw3 |
| 第 12 週 | 課程:Alternative definition 1~6 |
| 第 13 週 | 課程:中介效應分析複習1~5 作業:Hw4 |
| 第 14 週 | 課程:11:00~12:00練習題討論、交互作用分析1~6 |
| 第 15 週 | 期末考試 |
| 第 16 週 | 課程:小組期末論文報告 |
| 第 17 週 | 元旦連假 |
| 第 18 週 | 作業:論文書面報告 |
There is no required textbook for this course. Following books are recommended for further reading: 1.因果經濟學。作者:中室牧子、津川友介。悅知文化。 2.Hernán MA, Robins JM (2019). Causal Inference. Boca Raton: Chapman & Hall/CRC, forthcoming. It can be freely downloaded from the following website: https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ (Chapters 1~3, 6, and 7) 3.VanderWeele T. Explanation in Causal Inference: Methods for Mediation and Interaction: Oxford University Press; 2015. (Chapters 1, 2) 4.因果革命:人工智慧的大未來 (The Book of Why: The New Science of Cause and Effect)。 作者:朱迪亞・珀爾, 達納・麥肯錫(Judea Pearl, Dana Mackenzie)。行路出版社。 5.VanderWeele, Tyler J., and Stijn Vansteelandt. “Conceptual issues concerning mediation, interventions and composition.” Statistics and its Interface 2.4 (2009): 457-468. 6.VanderWeele, Tyler J., and Stijn Vansteelandt. “Odds ratios for mediation analysis for a dichotomous outcome.” American journal of epidemiology 172.12 (2010): 1339-1348. 7.VanderWeele, Tyler J., Stijn Vansteelandt, and James M. Robins. “Effect decomposition in the presence of an exposure-induced mediator-outcome confounder.” Epidemiology (Cambridge, Mass.) 25.2 (2014): 300.
- 地點
- Room 413, Assembly Building I
- 時間
- By appointment.
- 聯絡方式