COMBO: Correcting Misclassified Binary Outcomes in Association Studies (original) (raw)
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>.
| Version: | 1.1.0 |
|---|---|
| Depends: | R (≥ 4.2.0) |
| Imports: | dplyr (≥ 1.0.10), tidyr (≥ 1.2.1), Matrix (> 1.4-1), rjags (≥ 4-13), turboEM (≥ 2021.1), SAMBA (≥ 0.9.0), utils (≥ 4.2.0) |
| Suggests: | knitr (≥ 1.40), testthat (≥ 3.0.0), devtools (≥ 2.4.5), xtable (≥ 1.8.0) |
| Published: | 2024-07-06 |
| DOI: | 10.32614/CRAN.package.COMBO |
| Author: | Kimberly Hochstedler Webb [aut, cre] |
| Maintainer: | Kimberly Hochstedler Webb |
| License: | MIT + file |
| NeedsCompilation: | no |
| SystemRequirements: | JAGS (http://mcmc-jags.sourceforge.net) |
| Materials: | README |
| CRAN checks: | COMBO results |
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