SensSpec: 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)
)

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.

Arguments

data: A data frame in which contains 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 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: FALSE.
digits: Number of significant digits. Default: max(1L, getOption("digits") - 3L).

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.

Examples

Run this code

## 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)