DBM MRMC is an extension of LABMRMC from Charles Metz and MRMC from Kevin Berbaum and Donald Dorfman.  This beta edition of the program provides the PROPROC, CBM, and RSCORE curve-fitting algorithms as well as the option of using a nonparametric trapezoidal/Wilxocon approach.  The program will read either MRMC- or LABMMRMC-formatted data sets.  In addition, the user has the option of performing an area under the ROC curve analysis, a sensitivity at a given specificity analysis, and a specificity at a given sensitivity analysis (not all combinations of curve-fitting algorithm and type of analysis are available in the beta edition).  Also, a new ANOVA routine from Steve Hillis is used that provides random-reader random-case, fixed-reader random-case, and random-case fixed-reader analyses based on normalized pseudovalues.  It should be noted that the user must determine which ANOVA option is appropriate for her or his experimental design—all options are not appropriate for all experimental designs.

 

NOTE: The user should understand that this version of the program is a beta version, and that it may contain bugs that were not caught during testing.  The program is provided “as is” without warranty or guaranty.

 

Dorfman, D.D., Berbaum, K.S., & Metz, C.E. (1992). Receiver operating characteristic rating analysis: Generalization to the population of  readers and patients with the jackknife method. Investigative Radiology, 27, 723-731.

 

Dorfman, D.D., Berbaum, K.S., Lenth, R.V., Chen, Y.F., & Donaghy, B.A. (1998).  Monte Carlo validation of a multireader method for receiver operating characteristic discrete rating data: Factorial experimental design. Academic Radiology, 5, 591-602.

 

Hillis, S.L., & Berbaum, K.S. (2004). Power estimation for the Dorfman-Berbaum-Metz method. Academic Radiology, 11, 1260-1273.

 

Hillis, S.L., Obuchowski, N.A., Schartz, K.M., & Berbaum, K.S. (2005). A comparison of the Dorfman-Berbaum-Metz and Obuchowski-Rockette methods for receiver operating characteristic (ROC) data. Statistics in Medicine, 24, 1579-1607.  DOI:10.1002/sim.2024.

                

Hillis, S.L. (2005). Monte Carlo validation of the Dorfman-Berbaum-Metz method using normalized pseudovalues and less data-based model simplification. Academic Radiology, 12, 1534-1541  DOI:10.1016/j.acra.2005.07.012.