SensSpec: Calculate sensitivity and specificity

In MRMCbinary: Multi-Reader Multi-Case Analysis of Binary Diagnostic Tests

Calculate sensitivity and specificity

Description

SensSpec() is a function for calculating overall sensitivity and specificity, modality-specific sensitivity and specificity, and reader-specific sensitivity and specificity within each modality.

Usage

SensSpec(
  data,
  Modality,
  Reader,
  Case = NULL,
  D,
  Y,
  percentage = FALSE,
  digits = max(1L, getOption("digits") - 3L)
)

Arguments

data	A data frame containing the modality identifiers (Modality), the reader identifiers (Reader), the case identifiers (Case), the true disease status (D), and the binary diagnostic test result (Y).
Modality	Variable specifying the modality identifiers.
Reader	Variable specifying the reader identifiers.
Case	Variable specifying the case identifiers. This variable is not directly used in the calculation of sensitivity and specificity in SensSpec(). Default: NULL.
D	Variable specifying the true disease status, coded as 1 for diseased cases and 0 for non-diseased cases.
Y	Variable specifying the binary diagnostic test result, coded as 1 for test-positive results and 0 for test-negative results.
percentage	Logical indicating whether the results should be reported as percentages rather than decimal proportions. Default: FALSE.
digits	Number of significant digits used to format the reported results. Default: max(1L, getOption("digits") - 3L).

Value

An object of class SensSpec containing the following components:

Overall Result	Overall sensitivity and specificity.
Modality-specific Result	Modality-specific sensitivity and specificity.
Reader-specific Modality-specific Result	Reader- and modality-specific sensitivity and specificity.
digits	Number of significant digits used to format the reported results.
Readers	Unique reader identifiers in the input data.
Modalities	Unique modality identifiers in the input data.

The results for SensSpec objects can be printed with print.SensSpec.

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

print.SensSpec

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)

MRMCbinary documentation built on March 23, 2026, 5:07 p.m.