Falsification before Extrapolation in Causal Effect Estimation
Authors: Zeshan M Hussain, Michael Oberst, Ming-Chieh Shih, David Sontag
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We illustrate the properties of our approach on semi-synthetic and real world datasets, and show that it compares favorably to standard meta-analysis techniques. ... Our conclusions are supported by semi-synthetic experiments, based on the IHDP dataset, as well as real-world experiments, based on clinical trial and observational data from the Women s Health Initiative (WHI), that demonstrate various characteristics of our meta-algorithm. |
| Researcher Affiliation | Academia | Zeshan Hussain MIT CSAIL & IMES Cambridge, MA zeshanmh@mit.edu Michael Oberst MIT CSAIL & IMES Cambridge, MA moberst@mit.edu Ming-Chieh Shih National Dong Hwa University Hualien, Taiwan mcshih@gms.ndhu.edu.tw David Sontag MIT CSAIL & IMES Cambridge, MA dsontag@csail.mit.edu |
| Pseudocode | Yes | Algorithm 1 Extrapolated Pessimistic Confidence Sets |
| Open Source Code | Yes | For code and instructions on data access, please visit: https://github.com/clinicalml/rct-obs-extrapolation |
| Open Datasets | Yes | We generate semi-synthetic RCTs and observational datasets with covariates from the Infant Health and Development Program (IHDP)... as well as real-world experiments, based on clinical trial and observational data from the Women s Health Initiative (WHI). |
| Dataset Splits | Yes | To construct the subgroups, we consider all pairs of a selected set of binary covariates... We treat two of the subgroups as validation subgroups and two as extrapolated subgroups. |
| Hardware Specification | No | The paper does not mention any specific hardware (GPU, CPU, or cloud instance types) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific version numbers for any software dependencies or libraries used in the experiments. |
| Experiment Setup | Yes | Data generation parameters include K, r, mc, mb, cz, and the significance level . By default, we set K = 5, r = 10, mc = 4, mb = 3, cz = (0, 0, 2, 4, 6), and = 0.05. The full hyperparameter search is provided in Appendix F, and details of hyperparameter tuning can be found in Appendix C. |