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Produce maximum likelihood estimates of common accuracy statistics for multiple measurement methods when a gold standard is not available. An R implementation of the expectation maximization algorithms described in Zhou et al. (2011) <doi:10.1002/9780470906514> with additional functions for creating simulated data and visualizing results. Supports binary, ordinal, and continuous measurement methods.
Version: | 0.5.1 |
Imports: | stats, dplyr, ggplot2, purrr, tibble, tidyr, mvtnorm, methods, stringr, Rdpack |
Suggests: | knitr, rmarkdown |
Published: | 2024-02-20 |
DOI: | 10.32614/CRAN.package.emery |
Author: | Corie Drake [aut, cre, cph] |
Maintainer: | Corie Drake <therealcfdrake at gmail.com> |
License: | GPL (≥ 3) |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | emery results |
Reference manual: | emery.pdf |
Vignettes: |
emery |
Package source: | emery_0.5.1.tar.gz |
Windows binaries: | r-devel: emery_0.5.1.zip, r-release: emery_0.5.1.zip, r-oldrel: emery_0.5.1.zip |
macOS binaries: | r-release (arm64): emery_0.5.1.tgz, r-oldrel (arm64): emery_0.5.1.tgz, r-release (x86_64): emery_0.5.1.tgz, r-oldrel (x86_64): emery_0.5.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.