mrmc | R Documentation |
Estimation and comparison of ROC performance metrics for multi-reader multi-case studies.
mrmc(response, test, reader, case, data, cov = jackknife, design = NULL)
response |
response metric expressed in terms of a package-supplied
performance |
test |
variable of test identifiers. |
reader |
variable of reader identifiers. |
case |
variable of case identifiers. |
data |
data frame containing the |
cov |
function, function call, or character string naming the
|
design |
one of the following study designs: 1 = factorial, 2 = cases
nested within readers, 3 = cases nested within tests, or |
Readers and cases are treated as random factors by default. Either one may
be designated as fixed in calls to mrmc
with the syntax
fixed(<variable name>)
, where <variable name>
is the name of
the reader or case variable.
Returns an mrmc
class object with the following elements.
design
experimental study design: 1 = factorial, 2 = cases nested within readers, 3 = cases nested within tests.
vars
character names of the analysis factors and reader performance metric.
fixed
logicals indicating whether the reader and case factors are treated as fixed in the analysis.
aov
results from an ordinary analysis of variance.
data
data frame of computed reader performance metrics for the analysis of variance.
num_obs
number of case observations for each of the computed metrics.
cov
reader performance covariance matrix.
mrmc_data
data frame of case-specific reader ratings.
levels
character levels of the true case statuses.
Dorfman DD, Berbaum KS, and Metz CE (1992). Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method. Investigative Radiology, 27: 723–731.
Obuchowski NA and Rockette HE (1995). Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests: an ANOVA approach with dependent observations. Communications in Statistics–Simulation and Computation 24: 285–308.
Hillis SL, Obuchowski NA, Schartz KM, and Berbaum KS (2005). A comparison of the Dorfman-Berbaum-Metz and Obuchowski-Rockette methods for receiver operating characteristic (ROC) data. Statisticsin Medicine, 24: 1579–1607.
Hillis SL (2007). A comparison of denominator degrees of freedom methods for multiple observer ROC analysis. Statistics in Medicine, 26: 596–619.
Hillis SL, Berbaum KS, and Metz CE (2008). Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis. Academic Radiology, 15: 647–661.
metrics
, cov_methods
,
parameters
, plot
, roc_curves
,
summary
## Random readers and cases (est <- mrmc(empirical_auc(truth, rating), treatment, reader, case, data = VanDyke)) plot(est) summary(est) ## Fixed readers and random cases est <- mrmc(empirical_auc(truth, rating), treatment, fixed(reader), case, data = VanDyke) summary(est)
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