# RJafroc 1.3.2.9000 Unreleased

## Implemented extensive testing comparing RJafroc to Iowa software

• See test-StCompare2Iowa.R in testthat directory.
• Does line by line comparison of RJafroc to results of OR-DBM MRMC 2.51 Build 20181028 for VanDyke and Franken datasets.
• These, and many other tests, are run automatically every time the RJafroc software is checked using R CMD check.

## Note on discrepancy vis-a-vis Iowa software

• Noted was a discrepancy between Var(R) and Var(TR) values reported by OR-DBM MRMC 2.51 Build 20181028 and RJafroc for Franken dataset.
• Their code does not implement the required max(Cov2 - Cov3, 0) constraint while RJafroc does.
• RJafroc reports VarTR = -0.00068389146 while their code reports VarTR = -0.00071276.
• Specifically, msTR - Var + Cov1 + max(Cov2 - Cov3, 0) = -0.00068389146 and msTR - Var + Cov1 + Cov2 - Cov3 = -0.00071276.
• This also affects the VarR values (see block of comments in UtilVarComponentsOR near line 161). Cov1, Cov2, Cov3 and Var are the same between both codes.
• I am aware that these discrepancies do not affect sample size estimates, but can cause confusion for the code maintainer and the end user.

## Updated sample size routines

• 3 Papers by Hillis et al on SS estimation for ROC studies: 2004, 2011 and 2018
• Hillis SL, Berbaum KS (2004). Power Estimation for the Dorfman-Berbaum-Metz Method. Acad Radiol, 11, 1260–1273.
• Hillis SL, Obuchowski NA, Berbaum KS (2011). Power Estimation for Multireader ROC Methods: An Updated and Unified Approach. Acad Radiol, 18, 129–142.
• Hillis SL, Schartz KM (2018). Multireader sample size program for diagnostic studies: demonstration and methodology. Journal of Medical Imaging, 5(04).
• The sample size routines have been updated to reflect the most recent publication. The equations in the code now have documentation as to their source(s).
• The routines have also been checked using the Java calculator provided on the U of Iowa website (pss20190918.jar).
• Briefly, the procedure defaults to the OR method, even when DBM variance components are provided, in line with the recommendations in the 2011 paper. For continuity with prior work a LegacyCode flag is provided to force execution of the original DBM method (2004 paper).
• Added a few tests using the Franken dataset which yields negative Var(TR). Noticed a small difference in predicted power between forced DBM (0.78574588) and OR methods (0.8004469).
• Updated source of equations in SsPowerGivenJKDbmVarCom.
• The code rewrite was conducted on a new branch, UpdateSsRoutines off the developer branch.
• The changes were merged to the developer branch and then to the master branch.

## Major reorganization of dataset structure

• Instead of varying lengths for ROC/FROC, LROC and SPLIT-PLOT, all datasets now are lists of length 3, with each member (ratings, lesions, descriptions) consisting of sub-lists:
• ratings contain 3 elements: $NL, $LL and $LL_IL. • $lesions contains 3 elements: $perCase, $IDs and $weights. • $descriptions contains 7 elements: $fileName, $type, $name, $truthTableStr, $design, $modalityID and $readerID. • This considerably simplified the handling of different types of datasets. • The version number will be bumped to 2.0.0 on final submission to CRAN. • Since there are no downstream dependencies, I feel this big change is justified at this time. It will make it easier for me to maintain the code. • The code rewrite was conducted on a new branch, SimplifyDatasets off the developer branch. • The changes were merged to the developer branch and then to the master branch. ## Major simplifications to all significance testing St functions • Separated RRRC branches etc to separate files; likewise for DBM and OR branches, now the files are much shorter and easier to maintain • Changed returned data structure to a list of dataframes, see next comment; this makes for much cleaner and easier printing • Consistent returned objects from all St functions: list with data frames FOM, ANOVA, RRRC, FRRC and RRFC. • Output now closely follows that of Iowa software OR-DBM MRMC 2.51 which I ran using VmWare, Windows XP; Iowa software did not run on Windows 8 on two different machines (see below) • Ran detailed comparison to OR-DBM MRMC 2.51 and coded the checks in tests/testthat/test-St-Compare2Iowa.R for VanDyke dataset • Also visually compared RJafroc results against OR-DBM MRMC 2.51 for dataset04 converted to ROC (see Iowa code results in inst/Iowa/FedRoc.txt); • Shortened UtilOutputReport considerably, by using print(dataframe) instead of reading values from list or dataframe variables and then using sprintf with unreadable C-style format codes • Shortened SPLIT-PLOT analysis by returning Cov2 = Cov3 = 0 instead of NA • Confirmed that this gives same results as the version in master branch • Added vignettes back, rebuilt website • Passes all OSX checks except for file size NOTE: checking installed package size … NOTE installed size is 16.7Mb; sub-directories of 1Mb or more:doc 12.7Mb;extdata 1.3Mb • Marked regions of code requiring further inspection by TBA - handle this next • Will merge this code into master branch if it passes Travis ## Replaced stringsAsFactors = FALSE everywhere data.frame is used except … • Except in PlotEmpiricalOperatingCharacteristics, where factors and levels are used • Must specify this anytime the variable is used in a test as otherwise different versions will give factors or characters and not match those in goodValues folder • After old versions are phased out, this can be safely removed, as all versions will have this as the default • Setting options(stringsAsFactors = FALSE) at beginning of a function, e.g., StSignificanceTesting, passes this option onto called functions, e.g, StDBMHAnalyis • Use getOption("stringsAsFactors") to determine state of this option; must restart R to obtain default value (TRUE on the release version); calling a function that sets it to FALSE keeps the new value after exiting from function; must restart R again to get proper default. ## After repeated Travis failures • same issue; have to specify stringsAsFactors explicitly for each data.frame call, due to different defaults in different verions of R • Cannot set to TRUE at beginning of function, as in options("stringsAsFactors" = TRUE), as this is deprecated • Basically undid all changes in next note (see below) • passes R CMD check on OSX and Travis checks ## Removed stringsAsFactors arguments in all calls except… • In all calls to data.frame, except in plotting functions, PlotEmpiricalOperatingCharacteristics, where factors are used • In current R3.6.3 option($stringsAsFactors) = TRUE (stringsAsFactors is case sensitive!)
• This means that functions that don’t require factors, such as SsPowerTable() should set options(stringsAsFactors = FALSE) explicitly at the beginning of the code, in order to work in current and previous version of R (i.e., release and old-release)
• Functions that do use factors/levels such as plotting functions (PlotRsmOperatingCharacteristics and FitCorCbmRoc) should set options(stringsAsFactors = TRUE) in order to work in developer version of R, where default is options("stringsAsFactors") = FALSE
• This is all very confusing as I am having to dive into code written 6 years ago by someone else
• Going to test on Travis now

## Return transpose for foms member of StSignificanceTesting return object

• For consistency with OR DBM MRMC 2.51, and also for cleaner output, as number of treatments is usually less than number of readers
• Note added 5/30/20: this was undone; transpose is no longer used

## Moved official good value files to Dropbox

• They generate non-portable file name warning on R CMD check
• Moved VanDyke results to inst/IowaResults/VanDyke.txt

## Compared to latest official code

• mrmc_setup_w10_July_2019.exe; VanDyke VanDyke.lrc dataset; Dropobox/IowaSoftware/VanDyke.lrc
• OR DBM MRMC 2.51 <beta> Build 20181028 </beta> miplmrmc
• Software only runs under Windows XP
• Tried Windows 8 on different machines (iMac and MacBookPro) under VmWare Fusion; no luck, even after following directins twice on website
• Need to compare OR ouputs - WIP
• Need to fix documentation on StSignificanceTesting - WIP

## Discovered error

• For StSignificanceTesting(dataset02, method = "ORH", option = "FRRC") - done
• Need to put in testthat all combinations of method and option - done
• Different objects returned by StSignificanceTesting depending on choice of option - almost done
• Need to standardize as otherwise RJafrocBook is klutzy - WIP

## Added seed specification to UtilVarComponentOR

• Added seed specification to UtilVarComponentOR to allow comparison with RJafrocBook
• Added to tests: covEstMethod = jackknife, bootstrap and DeLong for two datasets
• dataset02 and dataset04 converted to ROC
• Will merge to master so that RJafrocBook code passes Travis

## Fixing significance testing with independent calculations in RJafrocBook

• Need to modify RJafroc to eliminate code duplication and improve style in all signficance testing functions - move this to issues
• I am only getting to understand it now (as I work on RJafrocBook)
• One reader case can now be handled by StSignificanceTesting(rocData1R, FOM = "Wilcoxon", method = "ORH")
• May not need StSignificanceTestingSingleFixedFactor which currently only handles DBMH method - add to issues
• Removed restriction of StSignificanceTesting to J > 1
• Will merge to master so that RJafrocBook code passes Travis

## Fixed error with msTC

• Found another error in msTC calculation in UtilMeanSquares
• Was trying to be too cute for my own good (collapsing two for-loops into one)
• Discoverd error while doing first principles calculation in RJafocBook, DBMH chapter, so there is at least one person who benefited from RJafrocBook
• Changed covEstMethod argument to ORH method to lower case (“jackknife” or “bootstrap”)

## Fixed issue with optim when flipping groups

• see issues #50 (closed) on RJafroc/master
• Allow a paramter of binormal model to be between -4 and 4
• Removed all vignettes; since these are now in RJafrocBook
• Removed all but one dataset (FZ_ALL.xlsx) from extdata/datasets so I dont get file size error (extdata was 2.5 MB, reduced to 1.3)

# RJafroc 1.3.2 2020-03-06

## After work on cran2-update work

• Copied altered files from R directory (which commented out examples which were taking lots of CPU time)
• Includes a correction to Compare3ProperRocFits.R
• Pulled out all vignettes (these have been moved to repository RJafrocBook)
• This gets file size below 5 MB

## Work post acceptance of v1.3.2, as of 3/7/20

• Going back to work interrupted by having to fix the errors on R-devel, see next section below.
• This is v1.3.2.9000
• Got all tests working! Resulted in fix to StDBMHAnalysis.R that fixed test that I had to skip on mac for context("SignificanceTestingAllCombinations"). Need to get this fix (lines 45-51) over to cran2 branch as I am thinking of splitting the package up by separating the cran2 branch as the base package RJafroc and depending on RJafroc for new package RJafroc2. This would solve the file size problems that I am running into. Just an idea.
• Current file size is 18.4 Mb!
• Synced with developer branch on GitHub and merged with master.

## After email from Kurt Hornik Kurt.Hornik@r-project.org

• Created new branch off cran2 1.3.1 called cran2-fix
• Bumped version to 1.3.2
• RJafroc failing on Linux
• r-devel-linux-x86_64-debian-clang
• r-devel-linux-x86_64-debian-gcc
• r-devel-linux-x86_64-fedora-clang (this showed up post email)
• r-devel-linux-x86_64-fedora-gcc (this showed up post email)
• Has to do with new default (R 4.0.0) for options(stringsAsFactors = FALSE)
• To recreate this problem in R CMD check I set options(stringsAsFactor=FALSE) near beginning of each plotting function (3 functions) using data.frame() and levels() to convert strings to factor levels
• To make problem go away I explicitly specified stringsAsFactor=TRUE in each call to data.frame() where necessary.
• Removed examples from FitCorCbmRoc() as they were generating excessive CPU time NOTES. Will need to add these to vignettes, later.
• Ran R CMD check successfully
• Ran all checks in ScriptsForCranSubmission.R
• Submitted to CRAN
• Accepted by CRAN
• See cran2-update/master branch for content relating to this version

## Modified UtilPseudoValues.R to work with SPLIT-PLOT data

• Created simulated SP datafile inst/extdata/toyFiles/FROC/FrocDataSpVaryK1K2.xlsx.
• Created simulated SP dataset datasetFROCSp corresponding to modalities 4,5 of dataset04
• Update vignette Ch00Vig5SimulateSplitPlotDataset.Rmd.
• Modified StORHAnalysis.R and to work with SP dataset provided method = "ORH" and covEstMethod = “jackknife” is used
• Corrected an error in analysis; see ~Dropbox/RJafrocChecks/StfrocSp.xlsx for details.
• Updated this file 2/19/20
• R CMD check successful … except for file size NOTE (18.4Mb)

## Created split plot dataset; update all datasets; confirm truthTableStr and DfReadDataFile()

• v1.3.1.9000
• created simulated split plot Excel dataset from Fed dataset: Ch00Vig5CreateSplitPlotDataset.Rmd; confirmed it is read without error!!
• updated datasets - see inst/FixRJafrocDatasets/ConvertDataset.R; worked on DfReadDataFile function
• Discoverd that .xls input does not work*; took it out as an allowed option; probably has to do with openxlsx
• checked truthTableStr with a data file that has only 1 and 3 lesions per case; was concerned about 4th dimension of truthTableStr; see Dropbox/RJafrocChecks/truthTableStr.xlsx for results of checks; note that fourth dimension will be 4, even though there are no cases with 2 lesions
• I think I need a separate vignette on truthTableStr - more for my sake
• added raw excel file datasets corresponding to included datasets to inst/extdata/datasets; found missing file SimulateFrocFromLrocDataset.R - not sure why I took it out;
• Added sheet AnnK to truthTableStr in Dropbox/RJafrocChecks
• Also tests that OldFormat file when read creates identical dataset to that created by NewFormat: basically two Excel fiies are identical except old format lacks the three extra columns; see checkDfReadDataFile.R
• Modified UtilFigureOfMerit to accomodate split plot dataset with varying number of cases for each reader
• Created a datafile inst/extdata/toyFiles/FROC/FrocDataSpVaryK1K2.xlsx that really exercises the DfReadDataFile function (case index is unsorted); resorted to data frames and sorting to successfully read it (it is used in three places - truthTableStr, NL and LL). See inst/extdata/testUtilFigureOfMerit/*.R for exercising files
• Need to include this file in tests
• Updated this file 2/10/20
• R CMD check successful

# RJafroc 1.3.1 2020-01-13

## Extended dataset object structure

• Bumped version number to 1.3.1 after corrections to DESCRIPTION file
• Version on CRAN is 1.3.1

## Extended dataset object structure

• Bumped version number to 1.3.0 as I am moving towards a CRAN submission
• Lost development branch while using GitHub; decided to do Git manually
• Why is .gitignore not working?
• Ann discovered bug in code: does not handle single reader properly
• Ann uncovered another bug in code: did not handle diseased cases first in Excel Truth sheet
• Both bugs have been fixed
• Make it easier to correlate the NL and LL values with those in the Excel file and catch data entry errors in DfReadDataFile()
• design = design,
• normalCases = normalCases,
• abnormalCases = abnormalCases,
• truthTableStr = truthTableStr
• Need to update all datasets and check all occurences where DfReadDataFile() is used
• Included my own CPP coded wAFROC plot function. Learning a lot form Dirk’s book website https://teuder.github.io/rcpp4everyone_en/.

## Split plot dataset

• Modifications to DfReadDataFile() to allow for split plot datasets completed.
• Must use newExcelFileFormat = TRUE as otherwise the code defaults to the old Excel format.
• The new format includes more stringent tests, IMHO, to catch data entry errors:
• TruthTableStr is created in checkTruthTable() which is used in subsequent read NL and LL worksheets.
• Work to be done to include split plot in significance testing.
• Corrected dataset03 which had -Infs for 1-ratings; need to check other ROC data files.
• Added vignettes describing data format using toyFiles and use of DfReadDataFile().
• Corrected error in old DfReadDataFile function.
• Passes R CMD check with file size note.

## Error in MS_TC corrected

• Noted by Erin Greco
• The missing “-1”: UtilMeanSquares() line 88 msTC <- msTC * J/((I - 1) * (Ktemp - 1)) has been corrected
• Reset goodValues values in test-StSignificance-testing.R at line 128

## Extended plotting function to LROC data

• PlotEmpiricalOperatingCharacteristics() now accepts ROC, FROC and LROC datasets.
• Simplified code.
• Included in unit tests.
• Added legend.position argument to allow better positioning of legend.

## Added FROC sample size vignettes and functions

• Ch19Vig1FrocSampleSize.Rmd: Compares FROC power to ROC power.
• Ch19Vig2FrocSampleSize.Rmd: FROC power calculation for a number of situations.
• SsFrocNhRsmModel(): constructs an RSM-based model, which allows one to relate an ROC effect size to a wAFROC effect size, and returns parameters of model to allow FOM estimation for ROC and wAFROC. Following functions are used to calculate the lesion distribution and lesion weights arrays:
• UtilLesionDistribution: renamed to UtilLesionDistr
• UtilLesionWeightsDistr:

## Significance testing functions

• StSignificanceTesting(): corrects errors affecting method = "ORH" and covEstMethod = "Jackknife". I messed up while trying to simplify XZ code. It calls:
• StDBMHAnalysis():
• StORHAnalysis():
• Ran Windows JAFROC on virtual Windows 8 machine and saved results (inst/VarCompDiscrepancy/includedFrocData_Inferred_ROC.txt) to validate current significance testing functions. Included unit tests in tests/testthat.
• Ran first XZ CRAN upload (version 0.0.1) code (StOldCode.R) to compare against current significance testing code. Included unit tests in tests/testthat.
• test-St-Compare2JAFROC.R: compares current code to Windows JAFROC results.
• test-St-Compare2Org.R: compares current code to RJafroc 0.0.1.
• test-St-CompareDBM2OR.R: compares current code DBM to current code OR results, when appropriate.

• gpfMyFOM(): interpolation error in LROC PCL and ALROC FOMs. Hand calculations showed that the approx function did not work for small datasets. Wrote my own simple interpolation code. See LrocFoms() in gpfMyFOM.R. See ChkLrocFoms.xlsx in inst/StSigTesting for details on hand calculation of LROC FOMs.
• LROC FOMs now apply to UtilFigureOfMerit() and all significance testing functions. These changes only affected values at small FPFValue, 0.2 or less.
• Most FOM related functions now accept FPFValue to accommodate LROC datasets.
• StSignificanceTestingCadVsRadiologists(): CAD results updated (only values for FPFValue 0.2 or less were affected); see CadFunctionTests.R in inst/CadTesting. See CadTestingNicoData.xlsx in inst/CadTesting. Included unit tests in tests/testthat.
• StSignificanceTestingCadVsRadiologists(): cleaned up and now runs all FOMs.
• SimulateLrocDataset(): FROC to LROC simulator based on RSM. Could be used for NH testing. RSM can now predict all paradigm data.
• DfFroc2Lroc(): Simulates an “AUC-equivalent” LROC dataset from an FROC dataset. This is neat!
• DfLroc2Froc(): Simulates an “AUC-equivalent” FROC dataset from an LROC dataset.
• DfLroc2Roc(): convert LROC dataset to ROC dataset.
• An error in dataset2ratings() has been corrected.

## Variance component input

• SignificanceTesting functions now accept variance components, without having to specify a dataset.

## Other affected functions and new functions:

• UtilVarComponentsDBM():
• UtilVarComponentsOR():
• SsPowerGivenJKDbmVarComp:
• SsPowerGivenJKOrVarComp:
• SsSampleSizeKGivenJ:
• SsPowerGivenJK:
• StSingleTreatmentRandomReader:
• Ensured that FPFValue argument immediately follows FOM, where applicable.

## Needs further testing

• StSignificanceTestingSingleFixedFactor:

## Extensions needed

• The addPlot routine in StSignificanceTestingCadVsRadiologists has been renamed to CadVsRadPlots(). It should be deprecated in future as PlotRsmOperatingCharacteristics() has more consistent visual output (and capabilities like handling lists of treatments and readers).
• Need a function that checks validity of FOM for dataset: isValidFom?
• Need to compare predicted curves for LROC and FROC data: does SimulateLrocDataset() predict both flattening out of LROC plot and wAFROC going to (1,1)?
• Split plot analysis

# RJafroc 1.2.0 2019-07-31

• Corrected all references to package name to RJafroc (note capitalization)
• Checked downstream dependencies - none as of July 23, 2019: revdep(“RJafroc”) yields character(0)
• Corrected error that was causing Solaris failure (Peter Philips)
• Corrected error in UtilPseudoValues.R that was caught by testthat
• Corrected StSignificanceTesting.R that was caught by testthat (Peter Philips)
• R CMD check generates testthat failure when run under RStudio, see following output, but not when run as devtools::test():
* checking tests ...
Running ‘testthat.R’ [158s/160s]
ERROR
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
Component "Source": Attributes: < Component "levels": 3 string mismatches >
List member = 2, Dataset = dataset02, FOM = Wilcoxon, method = DBMH

── 2. Failure: SignificanceTestingAllCombinations (@test-significance-te
CurrentValues[[listMem]] not equal to GoodValues[[listMem]].
Component "Source": Attributes: < Component "levels": 3 string mismatches >
List member = 2, Dataset = dataset05, FOM = HrAuc, method = DBMH

# RJafroc 1.1.0 2018-11-14

• Added travis-ci testing after each push; and build passing badges, etc.
• Removed dependence on caTools package, which was not being supported; extracted function trapz() from it and inserted directly into gpfMyFOM.R - see comments in that file of what led to this
• Removed dependence on xlsx package, which requires rJava and JAVA, replaced with dependence on openxlsx package. Was having difficulty installing rJava correctly after each OSX or R update.
• Corrected errors in UtilOutputReport.R.
• Fixed bug in UtilOutputReport that was preventing overwriting of existing output file, even when the user keys “y” in response to prompt
• Added correlated contaminated binormal model, CORCBM, fitting and related functions to make package current with 2017 CORCBM publication.
• Fixed error in PlotEmpiricalCharacteristics.R that was giving incorrect plots for other than ROC and wAFROC plots
• Added ChisqrGoodnessOfFit function, replacing 3 functions
• Cleaned up plotting code; using one function genericPlotROC.R instead of 3 functions
• Updated results of CBM, PROPROC and RSM fitting after discovering error in df calculation in RSM chisquare statistic; book results are wrong; only 2/236 fits yield a valid chisquare statistic
• Renamed ExampleCompare3ProperRocFits() to Compare3ProperRocFits()
• Corrected overwriting error in value returned by Compare3ProperRocFits()
• Added two vignettes: QuickStartDBMH and QuickStartDBMHExcelOutput
• Checked downstream dependencies - none as of Nov 11, 2018: revdep("rjafroc") yields character(0)

# RJafroc 1.0.2 2018-05-31

• StSignificanceTestingCadVsRadiologists was not working for different numbers of readers. As noted by Alejandro, the number of readers was hard coded. Fixed this and extended DfExtractDataset to include LROC datasets.
• Removed function SsFROCPowerGivenJK: FROC power is implemented in Online Appendix Chapter 19 (see email exchange with Kota Aoyagi)
• This version installed on SOLARIS!

# RJafroc 1.0.1 2018-02-18

• Package was not installing on Solaris - overloading errors. Changed sqrt(2) in RsmFuncs.cpp to sqrt(2.0). However, Solaris is incompatible with ggplot2; so will recommend that Solaris version not be distributed on CRAN.
• Sorry, but I’m not sure what’s different between the CRAN Solaris machine and R-hub’s Solaris machine. You could prepare a new package submission for CRAN with the caveat that, since you do not have access to a Solaris machine, your fix is speculative and may yet fail to compile on the CRAN Solaris machine.
• The CRAN Repository Policy (https://cran.r-project.org/web/packages/policies.html) also states:
Package authors should make all reasonable efforts to provide cross-platform portable code. Packages will not normally be accepted that do not run on at least two of the major R platforms. Cases for Windows-only packages will be considered, but CRAN may not be the most appropriate place to host them. So you could in theory argue your case that your package does not support Solaris, and request that CRAN not distribute your package on that platform. But given that the issue you’re bumping to is (not) documented explicitly in the R manuals, I’m not sure how much success you would have.

# RJafroc 1.0.0 2018-02-04

• Renamed functions for better organization;
• Removed shiny GUI interface
• Support for LROC datasets and cross-modality datasets

# RJafroc 0.1.1 2015-08-14

• An error in the p value calculation that gave incorrect p value (possibly exceeding one) when the first modality performed better than 2nd has been fixed. Thanks to Lucy D’Agostino McGowan for pointing out the error and the fix. This error, which does not occur in Windows version of JAFROC V 4.2.1, was not noticed as in all example files the 2nd modality performed better.

# RJafroc 0.1.0 2015-07-30

• A “shiny” based GUI has been added, accessed by the function RJafrocGui(). This allows a user only interested in analyzing a data file to access the underlying code in a “user friendly” way. The GUI is similar in functionality to that of Windows JAFROC 4.2.1 software.

• For the curve plotting functions, legend position and direction are automatically decided if they are not explicityly specified.

• The the output number of significant digits for statistical power in power table has been set to 3.

• Variance and covariance calculation error for ROI data has been fixed.

• A bug in the JAFROC data reading function that caused an error when encountering non-numeric values has been fixed.

• Floating point ratings are rounded to 6 significant digits when saving a dataset in JAFROC format.

• A bug in the plotting routine that affected plots for a single rating FROC dataset has been fixed.

• A bug in the plotting of AFROC curves for a dataset containing only non-diseased cases has been fixed.

# RJafroc 0.0.1 2015-04-24

• Original version posted to CRAN (by Xuetong Zhai)