Sensitivity Analysis for Difference in adjusted Restricted Mean Survival Time to Unmeasured Confounding
-
Updated
Oct 17, 2024 - R
#
unmeasured-confounding
Here are 6 public repositories matching this topic...
GSAMU: Sensitivity analysis for effects of multiple exposures in the presence of unmeasured confounding: non-Gaussian and time-to-event outcomes
-
Updated
Oct 23, 2024 - R
causarray is a Python module for simultaneous causal inference with an array of outcomes.
-
Updated
Mar 8, 2025 - Jupyter Notebook
Sensitivity analysis for effects of multiple exposures in the presence of unmeasured confounding
-
Updated
Jun 17, 2024 - R
Implementation of "A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes" (ICML)
reinforcement-learning partially-observable-environment off-policy-evaluation unmeasured-confounding
-
Updated
Jun 18, 2022 - Python
Implementation of "Off-Policy Interval Estimation with Confounded Markov Decision Process" (JASA, 2022+)
-
Updated
Mar 13, 2024 - Python
Improve this page
Add a description, image, and links to the unmeasured-confounding topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the unmeasured-confounding topic, visit your repo's landing page and select "manage topics."