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>.

Version:	1.2.0
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:	2024-10-30
DOI:	10.32614/CRAN.package.COMBO
Author:	Kimberly Hochstedler Webb [aut, cre]
Maintainer:	Kimberly Hochstedler Webb <kah343 at cornell.edu>
License:	MIT + file LICENSE
NeedsCompilation:	no
SystemRequirements:	JAGS (http://mcmc-jags.sourceforge.net)
Materials:	README
CRAN checks:	COMBO results

Documentation:

Reference manual:	COMBO.pdf
Vignettes:	COMBO Notation Guide (source, R code) COMBO Notation Guide - Two-stage Misclassification Model (source, R code)

Downloads:

Package source:	COMBO_1.2.0.tar.gz
Windows binaries:	r-devel: COMBO_1.2.0.zip, r-release: COMBO_1.2.0.zip, r-oldrel: COMBO_1.2.0.zip
macOS binaries:	r-release (arm64): COMBO_1.2.0.tgz, r-oldrel (arm64): COMBO_1.2.0.tgz, r-release (x86_64): COMBO_1.2.0.tgz, r-oldrel (x86_64): COMBO_1.2.0.tgz
Old sources:	COMBO archive

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