TrialSize (version 1.4)

Dose.Response.time.to.event: Linear Contrast Test for Time-to-Event Endpoint in dose response study

Description

Under the exponential survival model, let lambdai be the proportion hazard rate for group i.

\(\sum ci = 0\).

Ho: \( L(\mu) = \sum ci \times \lambda_i =0 \)

Ha: \( L(p) = \sum ci \times \lambda_i = \epsilon > 0 \)

Usage

Dose.Response.time.to.event(alpha, beta, T0, T, Ti, ci, fi)

Arguments

alpha

significance level

beta

power = 1-beta

T0

T0 is the accrual time period

T

T is the total trial duration

Ti

\(\lambda_i=log(2)/Ti\), Ti is the estimated median time for each group.

ci

a linear contrast coefficients ci with sum(ci)=0.

fi

fi=ni/n is the sample size fraction for the ith group

References

Chow SC, Shao J, Wang H. Sample Size Calculation in Clinical Research. New York: Marcel Dekker, 2003

Examples

# NOT RUN {

Ti=c(14,20,22,24);
ci=c(-6,1,2,3);

Example.11.3.1<-Dose.Response.time.to.event(alpha=0.05,beta=0.2,T0=9,T=16,Ti=Ti,ci=ci,fi=1/4)
Example.11.3.1
#412

fi1=c(1/9,2/9,2/9,2/9);
Example.11.3.2<-Dose.Response.time.to.event(alpha=0.05,beta=0.2,T0=9,T=16,Ti=Ti,ci=ci,fi=fi1)
Example.11.3.2
#814

fi2=c(1/2.919,0.711/2.919,0.634/2.919,0.574/2.919);
Example.11.3.3<-Dose.Response.time.to.event(alpha=0.05,beta=0.2,T0=9,T=16,Ti=Ti,ci=ci,fi=fi2)
Example.11.3.3
#349

# }