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: |
0.3.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
ggplot2, methods, mvtnorm, progress, tibble, trust |
| Suggests: |
knitr, rmarkdown |
| Published: |
2025-09-27 |
| DOI: |
10.32614/CRAN.package.MRMCaov |
| Author: |
Brian J Smith [aut, cre],
Stephen L Hillis [aut],
Lorenzo L Pesce [ctb] |
| Maintainer: |
Brian J Smith <brian-j-smith at uiowa.edu> |
| BugReports: |
https://github.com/brian-j-smith/MRMCaov/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/brian-j-smith/MRMCaov |
| NeedsCompilation: |
no |
| Citation: |
MRMCaov citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
MRMCaov results |
Documentation:
Downloads:
Reverse dependencies:
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