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BuyseTest (version 2.4.0)

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 than a random observation drawn from the other group (Mann-Whitney parameter). The net benefit and win ratio statistics, i.e. the difference and ratio between the probabilities relative to the intervention and control groups, can then also be estimated. 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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Install

install.packages('BuyseTest')

Monthly Downloads

803

Version

2.4.0

License

GPL-3

Issues

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Stars

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Maintainer

Brice Ozenne

Last Published

March 20th, 2023

Functions in BuyseTest (2.4.0)

getCount

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

Sensitivity Analysis for the Choice of the Thresholds
getIid

Extract the H-decomposition of the Estimator
getPairScore

Extract the Score of Each Pair
getSurvival

Extract the Survival and Survival Jumps
S4BuysePower-summary

Summary Method for Class "S4BuysePower"
S4BuyseTest-class

Class "S4BuyseTest" (output of BuyseTest)
S4BuyseTest-confint

Confidence Intervals for Model Parameters
S4BuyseTest-coef

Coef Method for Class "S4BuyseTest"
coef.BuyseTestAuc

Extract the AUC Value
as.data.table.performance

Convert Performance Objet to data.table
coef.BuyseTestBrier

Extract the Brier Score
confint.BuyseTestAuc

Extract the AUC value with its Confidence Interval
.colCumSum_cpp

Column-wise cumulative sum
getPseudovalue

Extract the pseudovalues of the Estimator
boot2pvalue

Compute the p.value from the distribution under H1
calcIntegralSurv2_cpp

C++ Function pre-computing the Integral Terms for the Peron Method in the survival case.
S4BuyseTest-summary

Summary Method for Class "S4BuyseTest"
auc

Estimation of the Area Under the ROC Curve (EXPERIMENTAL)
autoplot.sensitivity

Graphical Display for Sensitivity Analysis
confint.BuyseTestBrier

Extract the Brier Score with its Confidence Interval
.colCenter_cpp

Substract a vector of values in each column
.colMultiply_cpp

Multiply by a vector of values in each column
.rowCumSum_cpp

Row-wise cumulative sum
S4BuyseTest-show

Show Method for Class "S4BuyseTest"
iid.BuyseTestAuc

Extract the idd Decomposition for the AUC
.vcov.logit

Variance-covariance matrix for Logistic Regressions
constStrata

Strata creation
.rowMultiply_cpp

Multiply by a vector of values in each row
.calcIntegralSurv_cpp

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

Divide by a vector of values in each column
discreteRoot

Dichotomic search for monotone function
performanceResample

Uncertainty About Performance of a Classifier (EXPERIMENTAL)
performance

Assess Performance of a Classifier
iid.BuyseTestBrier

Extract the idd Decomposition for the Brier Score
iid.prodlim

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

Prediction with Time to Event Model
summary.performance

Summary Method for Performance Objects
.calcIntegralCif_cpp

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

Performing simulation studies with BuyseTest
.rowScale_cpp

Dividy by a vector of values in each row
.information.logit

Information for Logistic Regressions
validFCTs

Check Arguments of a function.
.score.logit

Score for Logistic Regressions
predict.logit

Predicted Probability with Influence Function
testArgs

Check Arguments Passed to BuyseTest
pnormexp

Cumulative Distribution Function of a Gaussian Variable Plus an Exponential Variable
pnormweibull

Cumulative Distribution Function of a Gaussian Variable Plus an Weibull Variable
qnormexp

Density of a Gaussian Variable Plus an Exponential Variable
simCompetingRisks

Simulation of Gompertz competing risks data for the BuyseTest
rbind.performance

Combine Resampling Results For Performance Objects
qnormweibull

Density of a Gaussian Variable Plus an Weibull Variable
.rowCenter_cpp

Substract a vector of values in each row
.rowCumProd_cpp

Apply cumprod in each row
internal-print

internal functions for BuyseTest - display
Simulate endpoints for GPC

Simulation of data for the BuyseTest
calcPeron

internal functions for BuyseTest - initialization
S4BuysePower-class

Class "S4BuysePower" (output of BuyseTest)
BuyseMultComp

Adjustment for Multiple Comparisons
BuyseTest-package

BuyseTest package: Generalized Pairwise Comparisons
BuyseTest.options-methods

Methods for the class "BuyseTest.options"
BuyseTest.options

Global options for BuyseTest package
BuyseTTEM

Time to Event Model
GPC_cpp

C++ function performing the pairwise comparison over several endpoints.
S4BuysePower-show

Show Method for Class "S4BuysePower"
BuyseTest.options-class

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

Generalized Pairwise Comparisons (GPC)