A FORTRAN Program to Analyze Multi-Reader, Multi-Modality ROC Data Statistical Method described in:

Obuchowski NA, Rockette HE. Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests: an ANOVA approach with dependent observations. Communications in Statistics - Simulations 1995; 24: 285-308.

Obuchowski NA. Multireader, multimodality receiver operating characteristic curve studies: hypothesis testing and sample size estimation using an analysis of variance approach with dependent observations. Academic Radiology 1995; 2: S22-S29.

Software written by Nancy A. Obuchowski, Ph.D., The Cleveland Clinic Foundation

To perform the computations of the Obuchowski-Rockette statistical method for multireader, multimodality ROC datasets. The inputted dataset should have the following specifications: N subjects without the condition ("normals") and M subjects with the condition ("diseased") each underwent I diagnostic tests. The results of the I diagnostic tests were interpreted by the same sample of J readers. The objective of the study is to compare the mean accuracies of readers in the I tests to determine if the accuracy of the I tests differ.


  1. We assume there is a gold standard that provides each patients' true diagnosis, i.e. distinguishes normal from abnormal patients without error.
  2. We assume that the readers interpreted the test results blinded to other test results and the gold standard result.
  3. We assume there is only one test result per patient, per reader, per diagnostic test. The following scenarios are not appropriate for this program: analysis of the test results of the two eyes of a patient, analysis of the test results of the two kidneys of a patient.
  4. We assume there is no missing datapoints.
  5. The program can accomodate either ordinal or continuous-scale test results.
  6. Under FORMAT A, the program estimates the area under the empirical ROC curve (so called "nonparametric estimate") and performs the necessary calculations using these estimates of accuracy.
    ***To use other estimates of the ROC area (e.g. binormal MLEs) or to use other measures of accuracy (e.g. partial area under the ROC curve), the data must be inputted using FORMAT B.
  7. The program treats the diagnostic tests as fixed effects, and the patient sample and readers as random effects.
  8. The program is currently dimensioned for either 2 or 3 modalities, up to 15 readers, and up to 500 patients with and 500 without the condition. These dimensions can be changed.
  9. The current name of the input file is 'obumrm_in.dat'. The current name of the output file is 'obumrm_out.dat'.
  10. There are example input and output files that can be used as templates for data entry and as verification that the program is performing properly.

Files for Downloading:
The following plain text files may be downloaded by clicking on the filenames.

ReadMe file on OBUMRM.FOR readme.txt

Instructions for using FORMAT A instructionsA.txt

formAordin.dat: An example input dataset in format A (ordinal-scale data)
formAcont.dat: An example input dataset in format A (continuous-scale data)

Instructions for using FORMAT B InstructionsB.txt
formB.dat: An example input dataset in format B

OBUMRM.FOR: The actual FORTRAN program obumrm.for
formAordin_out.dat: The output file corresponding to formAordin.dat
formAcont_out.dat: The output file corresponding to formAcont.dat
formB_out.dat: The output file corresponding to formB.dat