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 correct outcome classification occurs in at least 50% of observations. A description of the analysis methods is available in Hochstedler and Wells (2023) <doi:10.48550/arXiv.2303.10215>.

Version: 1.0.0
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), kableExtra (≥ 1.3.4)
Published: 2023-04-19
Author: Kimberly Hochstedler [aut, cre]
Maintainer: Kimberly Hochstedler <kah343 at cornell.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: COMBO results

Documentation:

Reference manual: COMBO.pdf
Vignettes: COMBO Notation Guide
COMBO Notation Guide - Two-stage Misclassification Model

Downloads:

Package source: COMBO_1.0.0.tar.gz
Windows binaries: r-devel: COMBO_1.0.0.zip, r-release: COMBO_1.0.0.zip, r-oldrel: COMBO_1.0.0.zip
macOS binaries: r-release (arm64): COMBO_1.0.0.tgz, r-oldrel (arm64): COMBO_1.0.0.tgz, r-release (x86_64): COMBO_1.0.0.tgz

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