EHRmuse
Multi-Cohort Selection Bias Correction using IPW and AIPW Methods
Comprehensive toolkit for addressing selection bias in binary disease models across diverse non-probability samples, each with unique selection mechanisms. It utilizes Inverse Probability Weighting (IPW) and Augmented Inverse Probability Weighting (AIPW) methods to reduce selection bias effectively in multiple non-probability cohorts by integrating data from either individual-level or summary-level external sources. The package also provides a variety of variance estimation techniques. Please refer to Kundu et al. <doi:10.48550/arXiv.2412.00228>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.2.2 |
rolling linux/jammy R-4.5 | EHRmuse_0.0.2.2.tar.gz |
174.1 KiB |
0.0.2.2 |
rolling linux/noble R-4.5 | EHRmuse_0.0.2.2.tar.gz |
174.1 KiB |
0.0.2.2 |
rolling source/ R- | EHRmuse_0.0.2.2.tar.gz |
32.5 KiB |
0.0.2.2 |
latest linux/jammy R-4.5 | EHRmuse_0.0.2.2.tar.gz |
174.1 KiB |
0.0.2.2 |
latest linux/noble R-4.5 | EHRmuse_0.0.2.2.tar.gz |
174.1 KiB |
0.0.2.2 |
latest source/ R- | EHRmuse_0.0.2.2.tar.gz |
32.5 KiB |
0.0.2.2 |
2026-04-26 source/ R- | EHRmuse_0.0.2.2.tar.gz |
32.5 KiB |
0.0.2.2 |
2026-04-23 source/ R- | EHRmuse_0.0.2.2.tar.gz |
32.5 KiB |
0.0.2.2 |
2026-04-09 windows/windows R-4.5 | EHRmuse_0.0.2.2.zip |
372.7 KiB |
0.0.2.1 |
2025-04-20 source/ R- | EHRmuse_0.0.2.1.tar.gz |
15.3 KiB |