SensSpec {MRMCbinary} | R Documentation |
Calculate sensitivity and specificity
Description
SensSpec()
is the function that calculates overall sensitivity and specificity, modality-specific sensitivity and specificity, and modality- and reader-specific sensitivity and specificity.
Usage
SensSpec(
data,
Modality,
Reader,
Case,
D,
Y,
percentage = FALSE,
digits = max(1L, getOption("digits") - 3L)
)
Arguments
data |
A data frame in which contains the modality identifiers ( |
Modality |
Variable of the modality identifiers. |
Reader |
Variable of the reader identifiers. |
Case |
Variable of the case identifiers. |
D |
Variable of the true disease status. It should be set the value to 1 for cases diseased and to 0 for those non-diseased. |
Y |
Variable of the binary diagnostic test result. It should be set the value to 1 for cases diagnosed as positive and to 0 for those diagnosed as negative. |
percentage |
Whether to report results as decimals or percentage points. Default: |
digits |
Number of significant digits. Default: |
Value
An object of class SensSpec
. The object is a data.frame with the following components:
Overall Result |
Overall sensitivity and specificity |
Modality-specific Result |
Modality-specific sensitivity and specificity |
Reader-specific Modality-specific Result |
Modality- and reader-specific sensitivity and specificity |
digits |
The number of significant digits |
The results for the SensSpec
are printed with the print.SensSpec
function.
References
Yerushalmy, J. (1947). Statistical Problems in Assessing Methods of Medical Diagnosis, with Special Reference to X-Ray Techniques. Public Health Reports (1896-1970), 62(40), 1432–1449.
See Also
Examples
## Load example data
data(VanDyke)
## Return the first parts of an object
head(VanDyke)
## Extract unique modalities
unique(VanDyke$treatment)
## Extract Unique readers
unique(VanDyke$reader)
## Create binary test results (Y_ijk)
VanDyke$Y <- as.numeric(VanDyke$rating >= 3)
## Example usage of SensSpec function:
# Report results as decimals
senspe_result1 <- SensSpec(data = VanDyke, Modality = treatment,
Reader = reader, Case = case,
D = truth, Y = Y, percentage = FALSE, digits = 3)
# Report results as percentage points
senspe_result2 <- SensSpec(data = VanDyke, Modality = treatment,
Reader = reader, Case = case,
D = truth, Y = Y, percentage = TRUE, digits = 1)