The function `survm_samplesize` calculates the sample size according to the distributional parameters of the responders and non-responders.
survm_samplesize(
ascale0_r,
ascale0_nr,
ascale1_r,
ascale1_nr,
delta_p,
p0,
m0_r,
m0_nr,
diffm_r,
diffm_nr,
S0_r,
S0_nr,
diffS_r,
diffS_nr,
Delta_r,
Delta_nr,
ascale_cens,
tau,
bshape0 = 1,
bshape1 = 1,
all_ratio = 0.5,
alpha = 0.025,
beta = 0.2,
set_param = 0
)scale parameter for the Weibull distribution in the control group for responders
scale parameter for the Weibull distribution in the control group for non-responders
scale parameter for the Weibull distribution in the intervention group for responders
scale parameter for the Weibull distribution in the intervention group for non-responders
effect size for the response rate
event rate for the response
survival mean for responders in the control group
survival mean for non-responders in the control group
difference in survival means between groups for responders
difference in survival means between groups for responders
tau-year survival rates for responders in the control group
tau-year survival rates for non-responders in the control group
difference in tau-year survival rates for responders
difference in tau-year survival rates for non-responders
restricted mean survival times (RMST) difference between intervention and control groups for responders
RMST difference between intervention and control groups for non-responders
distributional parameter for the exponential distribution for the censoring
follow-up
shape parameter for the Weibull distribution in the control group
shape parameter for the Weibull distribution in the intervention group
allocation ratio. The ratio of numbers of participants allocated in the control group. By default is assumed 1:1 (i.e., all_ratio=0.5)
type I error
type II error
Set of parameters to be used for the responders/non-responders survival functions If the set of parameters is =1, then the sample size is computed using the survival means (m0_r,m0_nr,diffm _r,diffm_nr); if set_param=2, it is computed using the tau-year survival rates (S0_r,S0_nr,diffS_r,diffS_nr); if set_param=2, it is computed using the RMSTs and survival rates (Delta_r,Delta_nr,S0_r,S0_nr). If set_param=0, the computation is based on the distributional parameters (ascale0_r, ascale0_nr, ascale1_r, ascale1_nr).
This function returns the total sample size needed and the expected effect size for overall survival (RMST difference between groups).
Design of phase III trials with long-term survival outcomes based on short-term binary results. Marta Bofill Roig, Yu Shen, Guadalupe Gomez Melis. arXiv:2008.12887