MRMCaov: Multi-Reader Multi-Case Analysis of Variance

Estimation and comparison of the performances of diagnostic tests in multi-reader multi-case studies where true case statuses (or ground truths) are known and one or more readers provide test ratings for multiple cases. Reader performance metrics are provided for area under and expected utility of ROC curves, likelihood ratio of positive or negative tests, and sensitivity and specificity. ROC curves can be estimated empirically or with binormal or binormal likelihood-ratio models. Statistical comparisons of diagnostic tests are based on the ANOVA model of Obuchowski-Rockette and the unified framework of Hillis (2005) <doi:10.1002/sim.2024>. The ANOVA can be conducted with data from a full factorial, nested, or partially paired study design; with random or fixed readers or cases; and covariances estimated with the DeLong method, jackknifing, or an unbiased method. Smith and Hillis (2020) <doi:10.1117/12.2549075>.

Version: 0.3.0
Depends: R (≥ 3.5.0)
Imports: ggplot2, methods, mvtnorm, progress, tibble, trust
Suggests: knitr
Published: 2023-01-10
Author: Brian J Smith [aut, cre], Stephen L Hillis [aut], Lorenzo L Pesce [ctb]
Maintainer: Brian J Smith <brian-j-smith at>
License: GPL-3
NeedsCompilation: no
Citation: MRMCaov citation info
Materials: README NEWS
CRAN checks: MRMCaov results


Reference manual: MRMCaov.pdf
Vignettes: MRMCaov for R User Guide


Package source: MRMCaov_0.3.0.tar.gz
Windows binaries: r-prerel:, r-release:, r-oldrel:
macOS binaries: r-prerel (arm64): MRMCaov_0.3.0.tgz, r-release (arm64): MRMCaov_0.3.0.tgz, r-oldrel (arm64): MRMCaov_0.3.0.tgz, r-prerel (x86_64): MRMCaov_0.3.0.tgz, r-release (x86_64): MRMCaov_0.3.0.tgz

Reverse dependencies:

Reverse imports: rocbc


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