NSH Lab Calendar
HSPH Department of Biostatistics
Schedule for Fall 2024
| Date | Topic | Paper | Presenter |
|---|---|---|---|
| 23rd September (Week 1) | Introduction to longitudinal causal infernece | Ch. 2 of Rytgaard (2020) | NSH |
| 7th October (Week 2) | Overview of semi-parametric estimation in causal inference | finish Ch. 2 of Rytgaard (2020), Sec. 3.1-3.2 of Rytgaard (2020), and Kennedy (2016) | SVB |
| 21st October (Week 3) | Building blocks of longitudinal causal inference | Ch. 19-21 of Hernán and Robins (2024) | CT |
| 4th November (Week 4) | Semi-parametric estimation in longitudinal causal models | Bang and Robins (2005), Kennedy (2022) (Ex. 7) and van der Laan and Gruber (2012) (Thm. 1) | CJ |
| 18th November (Week 5) | Double robustness, semi-parametrics, and information geometry | Ying (2024) (1st attempt) | NSH |
| 4th December (Week 6) | Influence functions: Visual communication and intuition | Fisher and Kennedy (2020) Susmann (2023) | CJ |
| 16th December (Week 7) | Double robustness, semi-parametrics, and information geometry | Ying (2024) (2nd attempt) | NH |
References
Bang, Heejung, and James M. Robins. 2005. “Doubly Robust Estimation in Missing Data and Causal Inference Models.” Biometrics 61 (4): 962–73. https://doi.org/10.1111/j.1541-0420.2005.00377.x.
Fisher, Aaron, and Edward H Kennedy. 2020. “Visually Communicating and Teaching Intuition for Influence Functions.” The American Statistician 75 (2): 162–72. https://doi.org/10.1080/00031305.2020.1717620.
Hernán, Miguel A, and James M Robins. 2024. Causal Inference: What If. CRC Press.
Kennedy, Edward H. 2016. “Semiparametric Theory and Empirical Processes in Causal Inference.” In Statistical Causal Inferences and Their Applications in Public Health Research, edited by Hua He, Pan Wu, and Ding-Geng (Din) Chen, 141–67. Springer. https://doi.org/10.1007/978-3-319-41259-7_8.
———. 2022. “Semiparametric Doubly Robust Targeted Double Machine Learning: A Review.” arXiv Preprint arXiv:2203.06469. https://doi.org/10.48550/arXiv.2203.06469.
Rytgaard, Helene Charlotte. 2020. “Targeted Causal Learning for Longitudinal Data.” PhD thesis, University of Copenhagen. https://biostat.ku.dk/dissertations/2020_rytgaard.pdf.
Susmann. 2023. “One Step Estimators and Pathwise Derivatives.” https://observablehq.com/@herbps10/one-step-estimators-and-pathwise-derivatives.
van der Laan, Mark J, and Susan Gruber. 2012. “Targeted Minimum Loss Based Estimation of Causal Effects of Multiple Time Point Interventions.” The International Journal of Biostatistics 8 (1).
Ying, Andrew. 2024. “A Geometric Perspective on Double Robustness by Semiparametric Theory and Information Geometry.” arXiv Preprint arXiv:2404.13960. https://arxiv.org/abs/2404.13960.