Package: BuyseTest 3.0.5

BuyseTest: Generalized Pairwise Comparisons

Implementation of the Generalized Pairwise Comparisons (GPC) as defined in Buyse (2010) <doi:10.1002/sim.3923> for complete observations, and extended in Peron (2018) <doi:10.1177/0962280216658320> to deal with right-censoring. GPC compare two groups of observations (intervention vs. control group) regarding several prioritized endpoints to estimate the probability that a random observation drawn from one group performs better/worse/equivalently than a random observation drawn from the other group. Summary statistics such as the net treatment benefit, win ratio, or win odds are then deduced from these probabilities. Confidence intervals and p-values are obtained based on asymptotic results (Ozenne 2021 <doi:10.1177/09622802211037067>), non-parametric bootstrap, or permutations. The software enables the use of thresholds of minimal importance difference, stratification, non-prioritized endpoints (O Brien test), and can handle right-censoring and competing-risks.

Authors:Brice Ozenne [aut, cre], Eva Cantagallo [aut], William Anderson [aut], Julien Peron [ctb], Johan Verbeeck [ctb]

BuyseTest_3.0.5.tar.gz
BuyseTest_3.0.5.zip(r-4.5)BuyseTest_3.0.5.zip(r-4.4)
BuyseTest_3.0.5.tgz(r-4.4-x86_64)BuyseTest_3.0.5.tgz(r-4.4-arm64)
BuyseTest_3.0.5.tar.gz(r-4.5-noble)BuyseTest_3.0.5.tar.gz(r-4.4-noble)
BuyseTest_3.0.5.tgz(r-4.4-emscripten)
BuyseTest.pdf |BuyseTest.html✨
BuyseTest/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/bozenne/buysetest/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

generalized-pairwise-comparisonsnon-parametricstatistics

5.72 score 4 stars 82 scripts 806 downloads 1 mentions 32 exports 105 dependencies

Last updated 1 months agofrom:fa46e50757. Checks:OK: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-win-x86_64OKNov 12 2024
R-4.5-linux-x86_64OKNov 12 2024
R-4.4-win-x86_64OKNov 12 2024
R-4.4-mac-x86_64OKNov 12 2024
R-4.4-mac-aarch64OKNov 12 2024

Exports:.calcIntegralCif_cpp.calcIntegralSurv_cppaucbrierBuyseMultCompBuyseTestBuyseTest.optionsBuyseTTEMcalcIntegralSurv2_cppCasinoTestcoefconfintconstStratagetCountgetIidgetPairScoregetPseudovaluegetSurvivalGPC_cppGPC2_cppmodel.tablesnobsperformanceperformanceResampleplotpowerBuyseTestprintsensitivityshowsimBuyseTestsimCompetingRiskssummary

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercmprskcodetoolscolorspacedata.tablediagramdigestdoParalleldoSNOWevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsfuturefuture.applyggplot2globalsgluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvmagrittrMASSMatrixMatrixModelsmemoisemetsmgcvmimemultcompmunsellmvtnormnlmennetnumDerivparallellypillarpkgconfigplotrixpolsplineprodlimprogressrPublishquantregR6rangerrappdirsRColorBrewerRcppRcppArmadilloRcppEigenriskRegressionrlangrmarkdownrmsrpartrstudioapisandwichsassscalesshapesnowSparseMSQUAREMstringistringrsurvivalTH.datatibbletimeregtinytexutf8vctrsviridisviridisLitewithrxfunyamlzoo

BuyseTest: overview

Rendered fromoverview.pdf.asisusingR.rsp::asison Nov 12 2024.

Last update: 2024-10-13
Started: 2019-11-14

BuyseTest: wilcoxon test

Rendered fromwilcoxonTest.pdf.asisusingR.rsp::asison Nov 12 2024.

Last update: 2024-06-14
Started: 2021-10-15

Readme and manuals

Help Manual

Help pageTopics
BuyseTest package: Generalized Pairwise ComparisonsBuyseTest-package
Substract a vector of values in each column.colCenter_cpp
Column-wise cumulative sum.colCumSum_cpp
Multiply by a vector of values in each column.colMultiply_cpp
Divide by a vector of values in each column.colScale_cpp
Substract a vector of values in each row.rowCenter_cpp
Apply cumprod in each row.rowCumProd_cpp
Row-wise cumulative sum.rowCumSum_cpp
Multiply by a vector of values in each row.rowMultiply_cpp
Dividy by a vector of values in each row.rowScale_cpp
Convert Performance Objet to data.tableas.data.table.performance
Estimation of the Area Under the ROC Curve (EXPERIMENTAL)auc
Graphical Display for GPCautoplot.S4BuyseTest
Estimation of the Brier Score (EXPERIMENTAL)brier
Adjustment for Multiple ComparisonsBuyseMultComp
Two-group GPCBuyseTest
Global options for BuyseTest packageBuyseTest.options
Class "BuyseTest.options" (global setting for the BuyseTest package)BuyseTest.options-class
Methods for the class "BuyseTest.options"alloc,BuyseTest.options-method BuyseTest.options-methods select,BuyseTest.options-method
Time to Event ModelBuyseTTEM BuyseTTEM.BuyseTTEM BuyseTTEM.formula BuyseTTEM.prodlim BuyseTTEM.survreg
Multi-group GPC (EXPERIMENTAL)CasinoTest
Extract the AUC Valuecoef.BuyseTestAuc
Extract the Brier Scorecoef.BuyseTestBrier
Extract the AUC value with its Confidence Intervalconfint.BuyseTestAuc
Extract the Brier Score with its Confidence Intervalconfint.BuyseTestBrier
Strata creationconstStrata
Extract the Number of Favorable, Unfavorable, Neutral, Uninformative pairsgetCount getCount,S4BuyseTest-method S4BuyseTest-getCount
Extract the H-decomposition of the EstimatorgetIid getIid,S4BuyseTest-method S4BuyseTest-getIid
Extract the Score of Each PairgetPairScore getPairScore,S4BuyseTest-method S4BuyseTest-getPairScore
Extract the pseudovalues of the EstimatorgetPseudovalue getPseudovalue,S4BuyseTest-method S4BuyseTest-getPseudovalue
Extract the Survival and Survival JumpsgetSurvival getSurvival,S4BuyseTest-method S4BuyseTest-getSurvival
Extract the idd Decomposition for the AUCiid.BuyseTestAuc
Extract the idd Decomposition for the Brier Scoreiid.BuyseTestBrier
Extract i.i.d. decomposition from a prodlim modeliid.prodlim
Assess Performance of a Classifierperformance
Uncertainty About Performance of a Classifier (EXPERIMENTAL)performanceResample
Graphical Display for Sensitivity Analysisautoplot.S3sensitivity plot.S3sensitivity
Performing simulation studies with BuyseTestpowerBuyseTest
Prediction with Time to Event Modelpredict.BuyseTTEM
Combine Resampling Results For Performance Objectsrbind.performance
Class "S4BuysePower" (output of BuyseTest)S4BuysePower-class
Extract Summary for Class "S4BuysePower"model.tables,S4BuysePower-method S4BuysePower-model.tables
Sample Size for Class "S4BuysePower"nobs,S4BuysePower-method S4BuysePower-nobs
Print Method for Class "S4BuysePower"print,S4BuysePower-method S4BuysePower-print
Show Method for Class "S4BuysePower"S4BuysePower-show S4BuyseTest-show show,S4BuysePower-method show,S4BuyseTest-method
Summary Method for Class "S4BuysePower"S4BuysePower-summary summary,S4BuysePower-method
Class "S4BuyseTest" (output of BuyseTest)S4BuyseTest-class
Extract Summary Statistics from GPCcoef,S4BuyseTest-method S4BuyseTest-coef
Extract Confidence Interval from GPCconfint,S4BuyseTest-method S4BuyseTest-confint
Extract Summary for Class "S4BuyseTest"model.tables,S4BuyseTest-method S4BuyseTest-model.tables
Sample Size for Class "S4BuyseTest"nobs,S4BuyseTest-method S4BuyseTest-nobs
Graphical Display for GPCplot,S4BuyseTest,ANY-method S4BuyseTest-plot
Print Method for Class "S4BuyseTest"print,S4BuyseTest-method S4BuyseTest-print
Summary Method for Class "S4BuyseTest"S4BuyseTest-summary summary,S4BuyseTest-method
Sensitivity Analysis for the Choice of the ThresholdsS4BuyseTest-sensitivity sensitivity sensitivity,S4BuyseTest-method
Simulation of data for the BuyseTestsimBuyseTest
Simulation of Gompertz competing risks data for the BuyseTestsimCompetingRisks
Summary Method for Performance Objectssummary.performance