VanDyke: Multi-reader multi-case dataset

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

Multi-reader multi-case dataset

Description

Example data from a study comparing the relative performance of cinematic presentation of magnetic resonance imaging (CINE MRI) and single spin-echo magnetic resonance imaging (SE MRI) for the detection of thoracic aortic dissection (Van Dyke et al., 1993).

Usage

VanDyke

Format

A data frame with 1140 rows and 7 variables:

reader

Reader identifiers for the five radiologists.

treatment

Treatment identifiers for the two imaging modalities.

case

Case identifiers for 114 cases.

case2

Example case identifiers representing cases nested within readers.

case3

Example case identifiers representing cases nested within treatments.

truth

Indicator for thoracic aortic dissection (i.e., true disease status): 1 = thoracic aortic dissection present, 0 = thoracic aortic dissection absent

rating

Five-point ratings given to case images by the radiologists (i.e., diagnostic test result): 1 = definitely no aortic dissection, 2 = probably no aortic dissection, 3 = unsure about aortic dissection, 4 = probably aortic dissection, or 5 = definitely aortic dissection

Details

This example compares the relative performance of CINE MRI and SE MRI in detecting thoracic aortic dissection. There are 45 patients with aortic dissection and 69 patients without aortic dissection, and all were imaged with both SE MRI and CINE MRI. This dataset is also available in the MRMCaov package. See Source.

Source

This data are available at https://perception.lab.uiowa.edu and https://github.com/brian-j-smith/MRMCaov/tree/master/data.

References

Van Dyke, C. W., White, R. D., Obuchowski, N. A., Geisinger, M. A., Lorig, R. J., & Meziane, M. A. (1993). Cine MRI in the diagnosis of thoracic aortic dissection. 79th RSNA Meetings. Chicago, IL, 28.

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)

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