Description Usage Arguments Author(s) References Examples
An approximation alternative to the regular prediction of the information/covariance based on the assumed survival functions.
| 1 2 3 4 5 6 7 8 | 
| t.star | The ending time of the cumulative informaiton or covariance prediciton. | 
| p | Treatment assignment probability. | 
| S1 | Survival function for the treatment group. | 
| S0 | Survival function for the control gorup. | 
| func | The integrand function. | 
| n.length | The number of intervals spitted to obtain the approximate integration. | 
Lili Wang
Hasegawa, T. (2016). Group sequential monitoring based on the weighted log‐rank test statistic with the Fleming–Harrington class of weights in cancer vaccine studies. Pharmaceutical statistics, 15(5), 412-419.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | # Examples for approx.I
eps<-2 # delayed effect
p<-0.5 #treatment assignment
tau<-18 # end of the study
R<-14 # accrual period [0,R]
lambda<-log(2)/6 # control group risk hazard
theta<-0.7 # hazard ratio
lambda.trt<- lambda*theta
rho<- 0 # parameter for the weights
gamma<-1 #parameter for the weights
S1<-function(x){
  ifelse(x>eps,exp(-theta*lambda*x)*getc(theta,lambda,eps),exp(-lambda*x))
  }
  S0<-function(x){
    exp(-lambda*x)
    }
    S_pool<-function(x){
      p*S1(x)+(1-p)*S0(x)
      }
      func<-function(x){
        min((tau-x)/R,1)*(S_pool(x)^rho*(1-S_pool(x))^gamma)^2
        }
 approx.I(t.star=tau,p,S1=S1,S0=S0,fun=func,n.length=1e6)
 I.1(rho,gamma,lambda,theta,eps,R,p,tau)
 # Change the cumulative information up to 10 instead of taus
 func2<-function(x){
   min((10-x)/R,1)*(S_pool(x)^rho*(1-S_pool(x))^gamma)^2
   }
   approx.I(t.star=10,p,S1=S1,S0=S0,fun=func2,n.length=1e6)
   I.1(rho,gamma,lambda,theta,eps,R,p,t.star=10)
   # Covariance approximation for two weights: 1 and G(0,1)
   rho1=rho2=0
   gamma1=0
   gamma2=1
   func3<-function(x){
  min((10-x)/R,1)*(S_pool(x)^rho1*(1-S_pool(x))^gamma1)*(S_pool(x)^rho2*(1-S_pool(x))^gamma2)
  }
  approx.I(t.star=10,p,S1=S1,S0=S0,fun=func3,n.length=1e6)
  I.1.cov(rho1,gamma1,rho2,gamma2,lambda,theta,eps,R,p,t.star=10)
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