Learn R Programming

PHeval (version 1.1)

testscore: Restrained adaptive test based on the standardized score process

Description

This function provides the statistic and the pvalue of the restrained adaptive test in Chauvel and OQuigley (2014).

Usage

testscore(formula, data, beta0=0, n_rep=10^6, digits=5)

Value

A table with 3 lines, one for each of the following test: distance from origin, area under the curve (AUC) and restrained adaptive tests. For each test, the value of the statistic and the p-value are given, with the specified number of digits.

Arguments

formula

A formula object or character string with the time and censoring status separated by "+" on the left hand side and the covariates separated by "+" on the right. For instance, if the time name is "Time", the censoring status is "Status" and the covariates are "Cov1" and "Cov2", the formula is "Time+Status~Cov1+Cov2". No interaction can be provided.

data

A data frame with the data. The censoring status should be 1 for failure and 0 for censoring. No missing data are accepted.

beta0

A vector of parameters to test in the null hypothesis H_0: beta = beta0. By default, beta0 = 0. Its length is the number of covariates. Each value corresponds to the regression coefficient for a covariate, in the same order as appearing in formula.

n_rep

An integer for the number of simulations for the estimation of the p-value. It must be higher than 10^5.

digits

An integer for the number of decimal places to be used in the results.

Author

Cecile Chauvel

Details

The program does not handle ties in the data. We suggest to randomly split the ties before using the program.

References

Chauvel, C, OQuigley, J (2014) Tests for comparing estimated survival functions. Biometrika
101, 3, 535 – 552.
Chauvel, C (2014). PhD thesis (in French): Processus empiriques pour l'inférence dans le
modèle de survie à risques non proportionnels.
Université Pierre et Marie Curie - Paris VI.

See Also

standscore plotscore

Examples

Run this code
library(survival)
data(ovarian)

#############################################
# Tests for H_0: beta = 0 for both age and rx covariates

testscore(formula=futime+fustat~age+rx,data=ovarian)

#############################################
# Tests for H_0: beta=  maximum partial likelihood estimator of beta in the Cox model

beta_cox=coxph(Surv(futime,fustat)~ age+rx,data=ovarian)$coeff

testscore(formula=futime+fustat~age+rx,data=ovarian,beta0=beta_cox)

Run the code above in your browser using DataLab