COMBO
Correcting Misclassified Binary Outcomes in Association Studies
Use frequentist and Bayesian methods to estimate parameters from a binary outcome misclassification model. These methods correct for the problem of "label switching" by assuming that the sum of outcome sensitivity and specificity is at least 1. A description of the analysis methods is available in Hochstedler and Wells (2023) <doi:10.48550/arXiv.2303.10215>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.0 |
rolling linux/jammy R-4.5 | COMBO_1.2.0.tar.gz |
670.3 KiB |
1.2.0 |
rolling linux/noble R-4.5 | COMBO_1.2.0.tar.gz |
670.2 KiB |
1.2.0 |
rolling source/ R- | COMBO_1.2.0.tar.gz |
361.3 KiB |
1.2.0 |
latest linux/jammy R-4.5 | COMBO_1.2.0.tar.gz |
670.3 KiB |
1.2.0 |
latest linux/noble R-4.5 | COMBO_1.2.0.tar.gz |
670.2 KiB |
1.2.0 |
latest source/ R- | COMBO_1.2.0.tar.gz |
361.3 KiB |
1.2.0 |
2026-04-26 source/ R- | COMBO_1.2.0.tar.gz |
361.3 KiB |
1.2.0 |
2026-04-23 source/ R- | COMBO_1.2.0.tar.gz |
361.3 KiB |
1.2.0 |
2026-04-09 windows/windows R-4.5 | COMBO_1.2.0.zip |
681.6 KiB |
1.2.0 |
2025-04-20 source/ R- | COMBO_1.2.0.tar.gz |
361.3 KiB |