| SM {HCTDesign} | R Documentation |
Sample size in terms of number of subjects in the experimental group
Description
Calculates the total number of subjects for the experimental group using the total number of events(d2max:the output from design functions) and the estimated failure probability based on the person level historical control data and proportional hazard assumption.
Usage
SM(time, event, d2max, opt = "KM", event_ind, ta, tf, delta)
Arguments
time |
event time vector from person level historical control data. |
event |
numeric vector indicating the status of event from person level historical control data. |
d2max |
maximum number of events in the experimental group calculated from the design function. |
opt |
the method of fitting survival curve-"log_normal" or "KM" (log-normal or Kaplan Meier). Default is "KM". |
event_ind |
numeric value indicating the occurrence of event. |
ta |
enrollment time. |
tf |
follow-up time. |
delta |
hazard ratio. |
Value
Returns the value of sample size.
Author(s)
Tushar Patni, Yimei Li, Jianrong Wu, and Arzu Onar-Thomas.
References
Wu J, Xiong X (2016). “Survival trial design and monitoring using historical controls.” Pharmaceutical Statistics, 15(5), 405-411.
Wu J, Li Y (2020). “Group sequential design for historical control trials using error spending functions.” Journal of Biopharmaceutical Statistics, 30(2), 351-363.
Examples
time<-c(20,65,12,50,58,65,45,44)
event<-c(1,0,0,0,1,1,1,1)
d2max=57
gg<-SM(time,event,d2max,opt="log_normal",ta=4,tf=3,delta=0.57,event_ind=1)