Original investigationMonte Carlo validation of a multireader method for receiver operating characteristic discrete rating data: Factorial experimental design
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Recurrent Thyroid Cancer Diagnosis. ROC Study of the Effect of a High-Resolution Head and Neck <sup>18</sup>F-FDG PET/CT Scan.
2014, Academic RadiologyCitation Excerpt :The DBM MRMC 2.32 software with the PROPROC fitting methodology was used for data analysis. The software was downloaded from the Medical Image Perception laboratory website (http://perception.radiology.uiowa.edu) and the Kurt Rossmann Laboratories for Radiologic Image Research website (http://www-radiology.uchicago.edu/krl/) (6–12). The same software was used to perform a statistical significance test at the 0.05 level and to estimate standard errors (SEs) and 95% confidence intervals (CIs).
Simulation of Unequal-Variance Binormal Multireader ROC Decision Data. An Extension of the Roe and Metz Simulation Model.
2012, Academic RadiologyCitation Excerpt :For nonparametric estimation continuous decision-variable values were used; for semiparametric estimation. decision values were transformed to ordinal discrete ratings, taking integer values from one to five, using the same cut points as Dorfman et al (2). In addition, trapezoid-rule AUC simulations were repeated with the number of normal cases tripled: 25 abnormals and 75 normals, 50 abnormals and 150 normals, and 100 abnormals and 300 normals.
Multi-reader ROC Studies with Split-plot Designs. A Comparison of Statistical Methods
2012, Academic RadiologyCitation Excerpt :We investigated scenarios in which the readers' average ROC area with the two modalities was the same (null hypothesis) and scenarios in which the readers' average ROC area with the two modalities increased by a small amount (0.030–0.032) (alternative hypothesis). The values for the variance components were selected from values used by Roe and Metz (27) and Dorfman et al (28). We generated test scores from an equal-variance binormal distribution (ie, binormal parameter b = 1); the same variance components were used for diseased and nondiseased patients.
Comparing the diagnostic performance of methods used in a full-factorial design multi-reader multi-case studies
2023, Computational Statistics
Supported in part by National Institutes of Health grants R01 CA 62362 (D.D.D., K.S.B., R.V.L., Y.F.C., B.D.) and R01 CA 42453 (D.D.D. and K.S.B.) and in part by U.S. Army Medical Research and Materiel Command grant DAMD17-96-1-6254 (D.D.D., K.S.B., R.V.L.).