Multi-Reader, Multi-Case Analysis Methods (ROC, Agreement, and Other Metrics)
Convert an MRMC data frame to a design matrix
Convert an MRMC data frame to a score matrix
Assign a group label to items in a vector
Convert a data frame with all needed factors to doIMRMC formatted data...
Delete a data frame column
MRMC analysis for arbitrary design dataset
MRMC analysis of the area under the ROC curve
MRMC analysis for arbitrary design dataset
Empirically average over multiple empirical ROC curves
Create a standard set of ROC curves from an MRMC data frame
Create empirical ROC curve
Create empirical ROC curve from an MRMC formatted data frame
Extract between-reader between-modality pairs of scores
Extract within-reader between-modality pairs of scores
Get between-reader, between-modality paired data from an MRMC data fra...
Import MRMC dataset from the web (https://github.com/DIDSR/iMRMC/wiki/...
Get a score from an MRMC data frame
Get within-reader, between-modality paired data from an MRMC data fram...
Initialize the l'Ecuyer random number generator
MRMC Analysis of Limits of Agreement using ANOVA
Rename a data frame column name or a list object name
Convert ROC data formatted for doIMRMC to TPF and FPF data formatted f...
Create a configuration object for the sim.gRoeMetz program
Simulate an MRMC data set of an ROC experiment comparing two modalitie...
Create a configuration object for the sim.NormalIG.Hierarchical functi...
Simulate an MRMC data set comparing two modalities by a hierarchical m...
Simulate an MRMC data set
Simulates a sample MRMC ROC experiment
Convert an MRMC data frame of successes to one formatted for doIMRMC
Convert a doIMRMC formatted data frame to a standard data frame with a...
Create the kernel and design matrices for uStat11
Create the kernel and design matrices for uStat11
Analysis of U-statistics degree 1,1
This software does Multi-Reader, Multi-Case (MRMC) analyses of data from imaging studies where clinicians (readers) evaluate patient images (cases). What does this mean? ... Many imaging studies are designed so that every reader reads every case in all modalities, a fully-crossed study. In this case, the data is cross-correlated, and we consider the readers and cases to be cross-correlated random effects. An MRMC analysis accounts for the variability and correlations from the readers and cases when estimating variances, confidence intervals, and p-values. The functions in this package can treat arbitrary study designs and studies with missing data, not just fully-crossed study designs. An overview of this software, including references presenting details on the methods, can be found here: <https://www.fda.gov/medical-devices/science-and-research-medical-devices/imrmc-software-do-multi-reader-multi-case-statistical-analysis-reader-studies>.