RJafroc 1.3.2

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

After initial comments from CRAN upon submission of version 1.3.0

• Changes to DESCRIPTION file (removed emphasis characters and url before <)
• Added a sentence on improved sample size routines
• Bumped version to 1.3.1

Extended dataset object structure

• Removed vignettes and tests from cran2 branch
• Updated cran-comments.md and checked on all platforms
• Ready to submit

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?
• Additional members added 12/27/2019 by DPC
• 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.

CAD and LROC

• 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

• 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

• 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

• 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

• 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

• Renamed functions for better organization;
• Removed shiny GUI interface
• Support for LROC datasets and cross-modality datasets
• CAD vs. radiologist analysis, both single modality and dual modality

RJafroc 0.1.1

• 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

• 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

• Original version posted to CRAN (by Xuetong Zhai)