varStandardizedEffectSize
, RandomizedBlocksAnalysis
, Kendalltaupb
, Cliffd
, calculatePhat
, Calc4GroupNPStats
, LaplaceDist
, simulateRandomizedDesignEffectSizes
, RandomExperimentSimulations
, simulateRandomizedBlockDesignEffectSizes
, RandomizedBlocksExperimentSimulations
, NP4GroupMetaAnalysisSimulation
, NP2GroupMetaAnalysisSimulation
, MetaAnalysisSimulations
, CalculateTheoreticalEffectSizes
, RandomizedDesignEffectSizes
, RandomizedBlockDesignEffectSizes
Data 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
,searchForIndustryRelevantGitHubProjects
MadeyskiLewowski.IndustryRelevantGitHubJavaProjects20190324
reproduceTablesOfPaperMetaAnalysisForFamiliesOfExperiments
ExtractMAStatistics
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.DocData
MadeyskiKitchenham.EUBASdata
and functions getEffectSizesABBA
, effectSizeCI
getTheoreticalEffectSizeVariancesABBA
getSimulationData
, plotOutcomesForIndividualsInEachSequenceGroup
, getEffectSizesABBA
, effectSizeCI
effectSizeCI
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)getSimulationData
plotOutcomesForIndividualsInEachSequenceGroup
getEffectSizesABBA
getEffectSizesABBAIgnoringPeriodEffect
reproduceSimulationResultsBasedOn500Reps1000Obs
percentageInaccuracyOfLargeSampleVarianceApproximation
proportionOfSignificantTValuesUsingCorrectAnalysis
proportionOfSignificantTValuesUsingIncorrectAnalysis
KitchenhamMadeyski.SimulatedCrossoverDataSets
backed by functions (varianceSimulation
, getSimulatedCrossoverDataSets
) to reproduce the data set.cloudOfWords
KitchenhamMadeyskiBudgen16.FINNISH
KitchenhamMadeyskiBudgen16.PolishSubjects
KitchenhamMadeyskiBudgen16.SubjectData
KitchenhamMadeyskiBudgen16.PolishData
KitchenhamMadeyskiBudgen16.DiffInDiffData
KitchenhamMadeyskiBudgen16.COCOMO
densityCurveOnHistogram
boxplotHV
boxplotAndDensityCurveOnHistogram
printXTable
cloudOfWords
reproduceForestPlotRandomEffects
reproduceMixedEffectsAnalysisWithEstimatedVarianceAndExperimentalDesignModerator
reproduceMixedEffectsAnalysisWithExperimentalDesignModerator
reproduceMixedEffectsForestPlotWithExperimentalDesignModerator
reproduceTableWithEffectSizesBasedOnMeanDifferences
reproduceTableWithPossibleModeratingFactors
reproduceTableWithSourceDataByCiolkowski
Ciolkowski09ESEM.MetaAnalysis.PBRvsCBRorAR
MadeyskiKitchenham.MetaAnalysis.PBRvsCBRorAR
Madeyski15EISEJ.StudProjects$STUD
data setMadeyski15SQJ.NDC
Madeyski15EISEJ.OpenProjects
Madeyski15EISEJ.PropProjects
Madeyski15EISEJ.StudProjects
and functions (for importing data, visualization and descriptive analyses):readExcelSheet
densityCurveOnHistogram
boxplotHV
boxplotAndDensityCurveOnHistogram
See the package homepage (https://madeyski.e-informatyka.pl/reproducible-research/) for documentation and examples.