rss {adaptIVPT} | R Documentation |
This function reestimates the sample size using mixed criterion required for target power, using binary search. The power (passing rate) function of mixed criterion testing lacks a closed-form expression. Thus, sample size (re-)estimation requires a binary search, after identifying an n
where the passing rate exceeds the desired level.
rss(n, r, S_WR, params = list(), nsim = 1000, ncores = NULL)
n |
The number of donors in each simulation. |
r |
The number of replicates from each donor for each simulated dataset. |
S_WR |
The estimated standard deviation of the reference measurements. The reference-scaled average bioequivalence approach is used if S_WR > 0.249 and the average bioequivalence approach otherwise. |
params |
(Optional) The list of true parameters to be assumed in data generation.
|
nsim |
(Optional) The number of total simulations to be conducted. Defaults to 1,000. |
ncores |
(Optional) The number of CPU cores to use for parallel processing (OpenMP). If R hasn't been installed with OpenMP configured, this will not take effect. When OpenMP is available, it should not exceed the number of existing cores. If unspecified, it will default to 2 cores or the number of existing cores, whichever is smaller. |
A list of lists
parameters
- A list of true parameter settings.
rss
- The reestimated sample size.
runtime
- The total elapsed time charged for the execution of the program.
Daeyoung Lim, daeyoung.lim@uconn.edu
Potvin, D., DiLiberti, C. E., Hauck, W. W., Parr, A. F., Schuirmann, D. J., & Smith, R. A. (2008). Sequential design approaches for bioequivalence studies with crossover designs. Pharmaceutical Statistics: The Journal of Applied Statistics in the Pharmaceutical Industry, 7(4), 245-262.
out <- rss(10, 6, S_WR = 0.22, nsim = 2)