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BuyseTest (version 3.3.3)

Generalized Pairwise Comparisons

Description

Implementation of the Generalized Pairwise Comparisons (GPC) as defined in Buyse (2010) for complete observations, and extended in Peron (2018) 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 ), 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.

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Version

Install

install.packages('BuyseTest')

Monthly Downloads

1,149

Version

3.3.3

License

GPL-3

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/bozenne/BuyseTest

Maintainer

Brice Ozenne

Last Published

July 24th, 2025

Functions in BuyseTest (3.3.3)

S4BuyseTest-nobs

Sample Size for Class "S4BuyseTest"

S4BuysePower-model.tables

Extract Summary for Class "S4BuysePower"

S4BuyseTest-class

Class "S4BuyseTest" (output of BuyseTest)

S4BuysePower-print

Print Method for Class "S4BuysePower"

S4BuyseTest-plot

Graphical Display for GPC

S4BuysePower-summary

Summary Method for Class "S4BuysePower"

S4BuyseTest-coef

Extract Summary Statistics from GPC

S4BuysePower-nobs

Sample Size for Class "S4BuysePower"

S4BuyseTest-confint

Extract Confidence Interval from GPC

S4BuyseTest-model.tables

Extract Summary for Class "S4BuyseTest"

Estimation of the Area Under the ROC Curve (EXPERIMENTAL)

as.data.table.performance

Convert Performance Objet to data.table

Estimation of the Brier Score (EXPERIMENTAL)

S4BuyseTest-print

Print Method for Class "S4BuyseTest"

S4BuyseTest-vcov

Extract Uncertainty from GPC

S4BuyseTest-summary

Summary Method for Class "S4BuyseTest"

S4BuysePower-show

Show Method for Class "S4BuysePower"

calcIntegralSurv2_cpp

C++ Function pre-computing the Integral Terms for the Peron Method in the survival case.

coef.BuyseTestAuc

Extract the AUC Value

coef.BuyseTestBrier

Extract the Brier Score

autoplot.S4BuyseTest

Graphical Display for GPC

N-of-1 trials with On-demand Sildenafil as a Treatment for Raynaud Phenomenon

Constrained Kaplan-Meier Estimator

confint.BuyseTestAuc

Extract the AUC value with its Confidence Interval

.calcIntegralCif_cpp

C++ Function Computing the Integral Terms for the Peron Method in the presence of competing risks (CR).

Column-wise cumulative sum

S4BuyseTest-update

Re-run two-group GPC

RCT In Metastatic Pancreatic Cancer Comparing Two Chemoterapy.

RCT In Chronic Heart Failure Assessing an Inhibitor of the Renin-Angiotensin System.

.rowCumProd_cpp

Apply cumprod in each row

.colMultiply_cpp

Multiply by a vector of values in each column

Substract a vector of values in each column

Strata creation

.calcIntegralSurv_cpp

C++ Function Computing the Integral Terms for the Peron Method in the survival case.

.rowMultiply_cpp

Multiply by a vector of values in each row

Rare disease trial

Substract a vector of values in each row

confint.BuyseTestBrier

Extract the Brier Score with its Confidence Interval

Extract the H-decomposition of the Estimator

Divide by a vector of values in each column

Extract the Number of Favorable, Unfavorable, Neutral, Uninformative pairs

Extract the Score of Each Pair

Dividy by a vector of values in each row

Sensitivity Analysis for the Choice of the Thresholds

iid.BuyseTestAuc

Extract the idd Decomposition for the AUC

iid.BuyseTestBrier

Extract the idd Decomposition for the Brier Score

simCompetingRisks

Simulation of Gompertz competing risks data for the BuyseTest

Row-wise cumulative sum

rbind.performance

Combine Resampling Results For Performance Objects

Inference using MOVER in match designs (EXPERIMENTAL)

predict.BuyseTTEM

Prediction with Time to Event Model

plot.S3sensitivity

Graphical Display for Sensitivity Analysis

Extract i.i.d. decomposition from a prodlim model

performanceResample

Uncertainty About Performance of a Classifier (EXPERIMENTAL)

Assess Performance of a Classifier

Extract the pseudovalues of the Estimator

Performing simulation studies with BuyseTest

Simulation of data for the BuyseTest

Extract the Survival and Survival Jumps

summary.performance

Summary Method for Performance Objects

Check Arguments of a function.

BuyseTest-package

BuyseTest package: Generalized Pairwise Comparisons

C++ function performing the pairwise comparison over several endpoints.

BuyseTest.options-methods

Methods for the class "BuyseTest.options"

Adjustment for Multiple Comparisons

S4BuysePower-class

Class "S4BuysePower" (output of BuyseTest)

Time to Event Model

BuyseTest.options

Global options for BuyseTest package

BuyseTest.options-class

Class "BuyseTest.options" (global setting for the BuyseTest package)

Multi-group GPC (EXPERIMENTAL)