calculateLargeSampleRandomizedDesignEffectSizes,
NP2GMetaAnalysisSimulation,
NP4GMetaAnalysisSimulation (fixed errors)calculatePhat,
calculateCliffdcalculate2GMdMRE,
calculate4GMdMREcalculateCliffd (added export)calculate2GMdMRE,
calculate4GMdMRE (fixed CentralPHatMdMRE
calculation)calculate2GMdMRE,
calculate4GMdMREsimulateRandomizedBlockDesignEffectSizes,
NP4GroupMetaAnalysisSimulation (now
NP4GMetaAnalysisSimulation),
RandomizedBlockDesignEffectSizes,
percentageInaccuracyOfLargeSampleVarianceApproximationNP4GMetaAnalysisSimulation, NP2GroupMetaAnalysisSimulation
now NP2GMetaAnalysisSimulation, Kendalltaupb now
calculateKendalltaupb, CalculateTheoreticalEffectSizes now
calculatePopulationStatisticsAnalyseResiduals calc.a
calc.b calcCliffdConfidenceIntervals
calcEffectSizeConfidenceIntervals
calcPHatConfidenceIntervals calculate2GMdMRE
calculate4GMdMRE calculateCliffd
calculateLargeSampleRandomizedDesignEffectSizes
calculateLargeSampleRandomizedBlockDesignEffectSizes
calculateNullESAccuracy CatchError
checkIfValidDummyVariable Cliffd.test
crossoverResidualAnalysis doLM
metaanalyseSmallSampleSizeExperiments
NP2GMetaAnalysisSimulation
NP4GMetaAnalysisSimulation PHat.test
simulate2GExperimentData
simulate4GExperimentData
testfunctionParameterChecksvarStandardizedEffectSize,
RandomizedBlocksAnalysis, Kendalltaupb,
Cliffd, calculatePhat,
Calc4GroupNPStats, LaplaceDist,
simulateRandomizedDesignEffectSizes,
RandomExperimentSimulations,
simulateRandomizedBlockDesignEffectSizes,
RandomizedBlocksExperimentSimulations,
NP4GroupMetaAnalysisSimulation,
NP2GroupMetaAnalysisSimulation,
MetaAnalysisSimulations,
CalculateTheoreticalEffectSizes,
RandomizedDesignEffectSizes,
RandomizedBlockDesignEffectSizesData set:
KitchenhamEtAl.CorrelationsAmongParticipants.Madeyski10,
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello17TOSEM,
KitchenhamEtAl.CorrelationsAmongParticipants.Ricca10TSE,
KitchenhamEtAl.CorrelationsAmongParticipants.Romano18ESEM,
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14JVLC,
KitchenhamEtAl.CorrelationsAmongParticipants.Reggio15SSM,
KitchenhamEtAl.CorrelationsAmongParticipants.Gravino15JVLC,
KitchenhamEtAl.CorrelationsAmongParticipants.Ricca14TOSEM,
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14EASE,
KitchenhamEtAl.CorrelationsAmongParticipants.Abrahao13TSE,
KitchenhamEtAl.CorrelationsAmongParticipants.Torchiano17JVLC,
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello15EMSE,
KitchenhamEtAl.CorrelationsAmongParticipants.Scanniello14TOSEM,
New functions including computational procedures used to
reproduce the main findings in a joint paper (planned to be submitted):
Barbara Kitchenham, Lech Madeyski, Giuseppe Scanniello and Carmine
Gravino, “The Importance of the Correlation in Crossover Experiments”:
CalculateRLevel1, ExtractGroupSizeData,
ConstructLevel1ExperimentRData,
ExtractExperimentData,
CalculateLevel2ExperimentRData,
ExtractSummaryStatisticsRandomizedExp,
calculateBasicStatistics,
calculateGroupSummaryStatistics,
rSimulations
MadeyskiLewowski.IndustryRelevantGitHubJavaProjects20191022
- over 15% of entries present in this data set is not present in the
previous data set
MadeyskiLewowski.IndustryRelevantGitHubJavaProjects20190324
due to moved time windows for the project creation and last push
dates.searchForIndustryRelevantGitHubProjects - now supports
flexible creation date and last push thresholds (enabling the script to
better support researchers interested in gathering evolving data
sets).transformHgtoZr,searchForIndustryRelevantGitHubProjectsMadeyskiLewowski.IndustryRelevantGitHubJavaProjects20190324reproduceTablesOfPaperMetaAnalysisForFamiliesOfExperimentsExtractMAStatistics function: it
works with metafor version 2.0-0, but changes to metafor’s
method of providing access to its individual results may introduce
errors into the function.calculateSmallSampleSizeAdjustment,
constructEffectSizes, transformRtoZr,
transformZrtoR, transformHgtoR,
calculateHg, transformRtoHg,
transformZrtoHgapprox, transformZrtoHg,
PrepareForMetaAnalysisGtoR,
ExtractMAStatistics,
aggregateIndividualDocumentStatistics,
reproduceTablesOfPaperMetaAnalysisForFamiliesOfExperiments.KitchenhamMadeyskiBrereton.MetaAnalysisReportedResults,
KitchenhamMadeyskiBrereton.ABBAMetaAnalysisReportedResults,
KitchenhamMadeyskiBrereton.ReportedEffectSizes,
KitchenhamMadeyskiBrereton.ABBAReportedEffectSizes
KitchenhamMadeyskiBrereton.ExpData, and
KitchenhamMadeyskiBrereton.DocDataMadeyskiKitchenham.EUBASdata and
functions getEffectSizesABBA,
effectSizeCIgetTheoreticalEffectSizeVariancesABBAgetSimulationData,
plotOutcomesForIndividualsInEachSequenceGroup,
getEffectSizesABBA, effectSizeCIeffectSizeCI to calculate 95% Confidence
Intervals (CI) on Standardised Effect Sizes (d) for cross-over
repeated-measures designsreproduceSimulationResultsBasedOn500Reps1000Obs function
(we agreed to write joint paper with Dr Curtin describing corrections to
his equations to calculate effect size variances for continuous outcomes
of cross-over clinical trials)getSimulationDataplotOutcomesForIndividualsInEachSequenceGroupgetEffectSizesABBAgetEffectSizesABBAIgnoringPeriodEffectreproduceSimulationResultsBasedOn500Reps1000ObspercentageInaccuracyOfLargeSampleVarianceApproximationproportionOfSignificantTValuesUsingCorrectAnalysisproportionOfSignificantTValuesUsingIncorrectAnalysisKitchenhamMadeyski.SimulatedCrossoverDataSets backed by
functions (varianceSimulation,
getSimulatedCrossoverDataSets) to reproduce the data
set.cloudOfWordsKitchenhamMadeyskiBudgen16.FINNISHKitchenhamMadeyskiBudgen16.PolishSubjectsKitchenhamMadeyskiBudgen16.SubjectDataKitchenhamMadeyskiBudgen16.PolishDataKitchenhamMadeyskiBudgen16.DiffInDiffDataKitchenhamMadeyskiBudgen16.COCOMOdensityCurveOnHistogramboxplotHVboxplotAndDensityCurveOnHistogramprintXTablecloudOfWordsreproduceForestPlotRandomEffectsreproduceMixedEffectsAnalysisWithEstimatedVarianceAndExperimentalDesignModeratorreproduceMixedEffectsAnalysisWithExperimentalDesignModeratorreproduceMixedEffectsForestPlotWithExperimentalDesignModeratorreproduceTableWithEffectSizesBasedOnMeanDifferencesreproduceTableWithPossibleModeratingFactorsreproduceTableWithSourceDataByCiolkowskiCiolkowski09ESEM.MetaAnalysis.PBRvsCBRorARMadeyskiKitchenham.MetaAnalysis.PBRvsCBRorARMadeyski15EISEJ.StudProjects$STUD data
setMadeyski15SQJ.NDCMadeyski15EISEJ.OpenProjectsMadeyski15EISEJ.PropProjectsMadeyski15EISEJ.StudProjects and functions (for
importing data, visualization and descriptive analyses):readExcelSheetdensityCurveOnHistogramboxplotHVboxplotAndDensityCurveOnHistogramSee the package homepage (https://madeyski.e-informatyka.pl/reproducible-research/) for documentation and examples.