Package: reproducer 0.6.0

Lech Madeyski

reproducer: Reproduce Statistical Analyses and Meta-Analyses

Includes data analysis and meta-analysis functions (e.g., to calculate effect sizes and 95% Confidence Intervals (CI) on Standardised Effect Sizes (d) for AB/BA cross-over repeated-measures experimental designs), data presentation functions (e.g., density curve overlaid on histogram),and the data sets analyzed in different research papers in software engineering (e.g., related to software defect prediction or multi- site experiment concerning the extent to which structured abstracts were clearer and more complete than conventional abstracts) to streamline reproducible research in software engineering.

Authors:Lech Madeyski [cre, aut, ctb], Barbara Kitchenham [aut, ctb], Tomasz Lewowski [aut, ctb], Marian Jureczko [ctb], David Budgen [ctb], Pearl Brereton [ctb], Jacky Keung [ctb], Stuart Charters [ctb], Shirley Gibbs [ctb], Amnart Pohthong [ctb], Giuseppe Scanniello [ctb], Carmine Gravino [ctb]

reproducer_0.6.0.tar.gz
reproducer_0.6.0.tar.gz(r-4.7-any)reproducer_0.6.0.tar.gz(r-4.6-any)
reproducer_0.6.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
reproducer/json (API)
NEWS

# Install 'reproducer' in R:
install.packages('reproducer', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.52 score 66 scripts 223 downloads 85 exports 75 dependencies

Last updated from:0a5b170451. Checks:4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK182
source / vignettesOK227
linux-release-x86_64OK166
wasm-releaseOK130

Exports:aggregateIndividualDocumentStatisticsAnalyseResidualsboxplotAndDensityCurveOnHistogramboxplotHVCalc4GroupNPStatscalcCliffdTestStatisticscalcPHatMATestStatisticscalculate2GBiascalculate2GType1Errorcalculate4GBiascalculate4GType1ErrorcalculateBasicStatisticscalculateCliffdcalculateGroupSummaryStatisticscalculateHgcalculateKendalltaupbcalculateLargeSampleRandomizedBlockDesignEffectSizescalculateLargeSampleRandomizedDesignEffectSizesCalculateLevel2ExperimentRDatacalculateMABiascalculateMAType1ErrorcalculateNullESAccuracycalculatePhatCalculateRLevel1calculateSmallSampleSizeAdjustmentCliffd.testconstructEffectSizesConstructLevel1ExperimentRDatacrossoverResidualAnalysisdensityCurveOnHistogrameffectSizeCIExtractExperimentDataExtractGroupSizeDataExtractMAStatisticsExtractSummaryStatisticsRandomizedExpfmtgetEffectSizesABBAgetEffectSizesABBAIgnoringPeriodEffectgetSimulationDatagetTheoreticalEffectSizeVariancesABBALaplaceDistmetaanalyse.Cliffdmetaanalyse.PHatmetaanalyseSmallSampleSizeExperimentsMetaAnalysisSimulationsNP2GMetaAnalysisSimulationNP4GMetaAnalysisSimulationpairedRankTestpairedSignTestpercentageInaccuracyOfLargeSampleVarianceApproximationPHat.testplotOutcomesForIndividualsInEachSequenceGroupPrepareForMetaAnalysisGtoRprintXTableproportionOfSignificantTValuesUsingCorrectAnalysisproportionOfSignificantTValuesUsingIncorrectAnalysisRandomExperimentSimulationsRandomizedBlockDesignEffectSizesRandomizedBlocksAnalysisRandomizedBlocksExperimentSimulationsRandomizedDesignEffectSizesreadExcelSheetreproduceForestPlotRandomEffectsreproduceMixedEffectsAnalysisWithEstimatedVarianceAndExperimentalDesignModeratorreproduceMixedEffectsAnalysisWithExperimentalDesignModeratorreproduceMixedEffectsForestPlotWithExperimentalDesignModeratorreproduceSimulationResultsBasedOn500Reps1000ObsreproduceTablesOfPaperMetaAnalysisForFamiliesOfExperimentsreproduceTableWithEffectSizesBasedOnMeanDifferencesreproduceTableWithPossibleModeratingFactorsreproduceTableWithSourceDataByCiolkowskirSimulationssearchForIndustryRelevantGitHubProjectssimulate2GExperimentDatasimulate4GExperimentDatasimulateRandomizedBlockDesignEffectSizessimulateRandomizedDesignEffectSizestransformHgtoRtransformHgtoZrtransformRtoHgtransformRtoZrtransformZrtoHgtransformZrtoHgapproxtransformZrtoRvarStandardizedEffectSize

Dependencies:askpassbitbit64bootclicliprcpp11crayoncurldigestdplyrfarvergenericsGetoptLongggplot2GlobalOptionsgluegridExtragtablehmshttrisobandjsonlitelabelinglatticelifecyclelme4magrittrMASSmathjaxrMatrixmetadatmetaformimeminqanlmenloptrnortestnumDerivopensslopenxlsxpbapplypillarpkgconfigplyrprettyunitsprogresspurrrR6rbibutilsRColorBrewerRcppRcppEigenRdpackreadrreformulasreshaperjsonrlangS7scalesstringistringrsystibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithrxtablezip

Readme and manuals

Help Manual

Help pageTopics
aggregateIndividualDocumentStatisticsaggregateIndividualDocumentStatistics
AnalyseResidualsAnalyseResiduals
boxplotAndDensityCurveOnHistogramboxplotAndDensityCurveOnHistogram
boxplotHVboxplotHV
calc.acalc.a
calc.bcalc.b
Calc4GroupNPStatsCalc4GroupNPStats
calcCliffdConfidenceIntervalscalcCliffdConfidenceIntervals
calcCliffdTestStatisticscalcCliffdTestStatistics
calcEffectSizeConfidenceIntervalscalcEffectSizeConfidenceIntervals
calcPHatConfidenceIntervalscalcPHatConfidenceIntervals
calcPHatMATestStatisticscalcPHatMATestStatistics
calculate2GBiascalculate2GBias
calculate2GType1Errorcalculate2GType1Error
calculate4GBiascalculate4GBias
calculate4GType1Errorcalculate4GType1Error
calculateBasicStatisticscalculateBasicStatistics
calculateCliffdcalculateCliffd
calculateGroupSummaryStatisticscalculateGroupSummaryStatistics
calculateHgcalculateHg
@title calculateKendalltaupb @description Computes point bi-serial version of Kendall's tau plus a 1-alpha confidence interval using the method recommended by Long and Cliff (1997). The algorithm is based on Wilcox's code but was extended to return the consistent variance and the confidence intervals based on the t-distribution. Also added a Diagnostic parameter to output internal calculations.calculateKendalltaupb
calculateLargeSampleRandomizedBlockDesignEffectSizescalculateLargeSampleRandomizedBlockDesignEffectSizes
calculateLargeSampleRandomizedDesignEffectSizescalculateLargeSampleRandomizedDesignEffectSizes
CalculateLevel2ExperimentRDataCalculateLevel2ExperimentRData
calculateMABiascalculateMABias
calculateMAType1ErrorcalculateMAType1Error
calculateNullESAccuracycalculateNullESAccuracy
calculatePhatcalculatePhat
calculatePopulationStatisticscalculatePopulationStatistics
CalculateRLevel1CalculateRLevel1
calculateSmallSampleSizeAdjustmentcalculateSmallSampleSizeAdjustment
CatchErrorCatchError
checkIfValidDummyVariablecheckIfValidDummyVariable
Ciolkowski09ESEM.MetaAnalysis.PBRvsCBRorAR dataCiolkowski09ESEM.MetaAnalysis.PBRvsCBRorAR
Cliffd.testCliffd.test
constructEffectSizesconstructEffectSizes
ConstructLevel1ExperimentRDataConstructLevel1ExperimentRData
crossoverResidualAnalysiscrossoverResidualAnalysis
densityCurveOnHistogramdensityCurveOnHistogram
doLMdoLM
effectSizeCIeffectSizeCI
ExtractExperimentDataExtractExperimentData
ExtractGroupSizeDataExtractGroupSizeData
ExtractMAStatisticsExtractMAStatistics
ExtractSummaryStatisticsRandomizedExpExtractSummaryStatisticsRandomizedExp
fmtfmt
getEffectSizesABBAgetEffectSizesABBA
getEffectSizesABBAIgnoringPeriodEffectgetEffectSizesABBAIgnoringPeriodEffect
getSimulationDatagetSimulationData
getTheoreticalEffectSizeVariancesABBAgetTheoreticalEffectSizeVariancesABBA
KitchenhamEtAl.CorrelationsAmongParticipants.Abrahao13TSE dataKitchenhamEtAl.CorrelationsAmongParticipants.Abrahao13TSE
KitchenhamEtAl.CorrelationsAmongParticipants.Gravino15JVLC dataKitchenhamEtAl.CorrelationsAmongParticipants.Gravino15JVLC
KitchenhamEtAl.CorrelationsAmongParticipants.Madeyski10 dataKitchenhamEtAl.CorrelationsAmongParticipants.Madeyski10
KitchenhamEtAl.CorrelationsAmongParticipants.Reggio15SSM dataKitchenhamEtAl.CorrelationsAmongParticipants.Reggio15SSM
KitchenhamEtAl.CorrelationsAmongParticipants.Ricca10TSE dataKitchenhamEtAl.CorrelationsAmongParticipants.Ricca10TSE
KitchenhamEtAl.CorrelationsAmongParticipants.Ricca14TOSEM dataKitchenhamEtAl.CorrelationsAmongParticipants.Ricca14TOSEM
KitchenhamEtAl.CorrelationsAmongParticipants.Romano18ESEM dataKitchenhamEtAl.CorrelationsAmongParticipants.Romano18ESEM
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14EASE dataKitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14EASE
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14JVLC dataKitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14JVLC
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14TOSEM dataKitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14TOSEM
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello15EMSE dataKitchenhamEtAl.CorrelationsAmongParticipants.Scanniello15EMSE
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello17TOSEM dataKitchenhamEtAl.CorrelationsAmongParticipants.Scanniello17TOSEM
KitchenhamEtAl.CorrelationsAmongParticipants.Torchiano17JVLC dataKitchenhamEtAl.CorrelationsAmongParticipants.Torchiano17JVLC
KitchenhamMadeyski.SimulatedCrossoverDataSets dataKitchenhamMadeyski.SimulatedCrossoverDataSets
KitchenhamMadeyskiBrereton.ABBAMetaAnalysisReportedResults dataKitchenhamMadeyskiBrereton.ABBAMetaAnalysisReportedResults
KitchenhamMadeyskiBrereton.ABBAReportedEffectSizes dataKitchenhamMadeyskiBrereton.ABBAReportedEffectSizes
KitchenhamMadeyskiBrereton.DocData dataKitchenhamMadeyskiBrereton.DocData
KitchenhamMadeyskiBrereton.ExpData dataKitchenhamMadeyskiBrereton.ExpData
KitchenhamMadeyskiBrereton.MetaAnalysisReportedResults dataKitchenhamMadeyskiBrereton.MetaAnalysisReportedResults
KitchenhamMadeyskiBrereton.ReportedEffectSizes dataKitchenhamMadeyskiBrereton.ReportedEffectSizes
KitchenhamMadeyskiBudgen16.COCOMO dataKitchenhamMadeyskiBudgen16.COCOMO
KitchenhamMadeyskiBudgen16.DiffInDiffData dataKitchenhamMadeyskiBudgen16.DiffInDiffData
KitchenhamMadeyskiBudgen16.FINNISH dataKitchenhamMadeyskiBudgen16.FINNISH
KitchenhamMadeyskiBudgen16.PolishData dataKitchenhamMadeyskiBudgen16.PolishData
KitchenhamMadeyskiBudgen16.PolishSubjects dataKitchenhamMadeyskiBudgen16.PolishSubjects
KitchenhamMadeyskiBudgen16.SubjectDataKitchenhamMadeyskiBudgen16.SubjectData
LaplaceDistLaplaceDist
Madeyski15EISEJ.OpenProjects dataMadeyski15EISEJ.OpenProjects
Madeyski15EISEJ.PropProjects dataMadeyski15EISEJ.PropProjects
Madeyski15EISEJ.StudProjects dataMadeyski15EISEJ.StudProjects
Madeyski15SQJ.NDC dataMadeyski15SQJ.NDC
MadeyskiKitchenham.EUBASdata dataMadeyskiKitchenham.EUBASdata
MadeyskiKitchenham.MetaAnalysis.PBRvsCBRorAR dataMadeyskiKitchenham.MetaAnalysis.PBRvsCBRorAR
MadeyskiLewowski.IndustryRelevantGitHubJavaProjects20190324 dataMadeyskiLewowski.IndustryRelevantGitHubJavaProjects20190324
MadeyskiLewowski.IndustryRelevantGitHubJavaProjects20191022 dataMadeyskiLewowski.IndustryRelevantGitHubJavaProjects20191022
metaanalyse.Cliffdmetaanalyse.Cliffd
metaanalyse.PHatmetaanalyse.PHat
metaanalyseSmallSampleSizeExperimentsmetaanalyseSmallSampleSizeExperiments
MetaAnalysisSimulationsMetaAnalysisSimulations
Patient Global Impression (PGI) data from Munzel and Brunner (2002)MunzelBrunner02.PGI
NP2GMetaAnalysisSimulationNP2GMetaAnalysisSimulation
NP4GMetaAnalysisSimulationNP4GMetaAnalysisSimulation
pairedRankTestpairedRankTest
pairedSignTestpairedSignTest
percentageInaccuracyOfLargeSampleVarianceApproximationpercentageInaccuracyOfLargeSampleVarianceApproximation
PHat.testPHat.test
PHatonesidedTestStatisticsPHatonesidedTestStatistics
PHattwosidedTestStatisticsPHattwosidedTestStatistics
plotOutcomesForIndividualsInEachSequenceGroupplotOutcomesForIndividualsInEachSequenceGroup
PrepareForMetaAnalysisGtoRPrepareForMetaAnalysisGtoR
printXTableprintXTable
proportionOfSignificantTValuesUsingCorrectAnalysisproportionOfSignificantTValuesUsingCorrectAnalysis
proportionOfSignificantTValuesUsingIncorrectAnalysisproportionOfSignificantTValuesUsingIncorrectAnalysis
RandomExperimentSimulationsRandomExperimentSimulations
RandomizedBlockDesignEffectSizesRandomizedBlockDesignEffectSizes
RandomizedBlocksAnalysisRandomizedBlocksAnalysis
title RandomizedBlocksExperimentSimulations description This function performs multiple simulations of 4 group balanced randomised Block experiments with two control groups and two treatment groups where one control group and one treatment group are assigned to block 1 and the other control group and treatment group are assigned to block 2. The simulations are based on one of four distributions and a specific group size. The function identifies the average value of the non-parametric effect sizes P-hat, Cliff' d and their variances and whether ot not the statistics were significant at the 0.05 level. We also present the values of the t-test as a comparison.RandomizedBlocksExperimentSimulations
RandomizedDesignEffectSizesRandomizedDesignEffectSizes
readExcelSheetreadExcelSheet
reproduceForestPlotRandomEffects()reproduceForestPlotRandomEffects
reproduceMixedEffectsAnalysisWithEstimatedVarianceAndExperimentalDesignModerator()reproduceMixedEffectsAnalysisWithEstimatedVarianceAndExperimentalDesignModerator
reproduceMixedEffectsAnalysisWithExperimentalDesignModerator()reproduceMixedEffectsAnalysisWithExperimentalDesignModerator
reproduceMixedEffectsForestPlotWithExperimentalDesignModerator()reproduceMixedEffectsForestPlotWithExperimentalDesignModerator
reproduceSimulationResultsBasedOn500Reps1000ObsreproduceSimulationResultsBasedOn500Reps1000Obs
reproduceTablesOfPaperMetaAnalysisForFamiliesOfExperimentsreproduceTablesOfPaperMetaAnalysisForFamiliesOfExperiments
reproduceTableWithEffectSizesBasedOnMeanDifferences()reproduceTableWithEffectSizesBasedOnMeanDifferences
reproduceTableWithPossibleModeratingFactors()reproduceTableWithPossibleModeratingFactors
reproduceTableWithSourceDataByCiolkowskireproduceTableWithSourceDataByCiolkowski
rSimulationsrSimulations
searchForIndustryRelevantGitHubProjectssearchForIndustryRelevantGitHubProjects
simulate2GExperimentDatasimulate2GExperimentData
simulate4GExperimentDatasimulate4GExperimentData
simulateRandomizedBlockDesignEffectSizessimulateRandomizedBlockDesignEffectSizes
simulateRandomizedDesignEffectSizessimulateRandomizedDesignEffectSizes
testfunctionParameterCheckstestfunctionParameterChecks
transformHgtoRtransformHgtoR
transformHgtoZrtransformHgtoZr
transformRtoHgtransformRtoHg
transformRtoZrtransformRtoZr
transformZrtoHgtransformZrtoHg
transformZrtoHgapproxtransformZrtoHgapprox
transformZrtoRtransformZrtoR
varStandardizedEffectSizevarStandardizedEffectSize