sim_power_best_norm_rank {ssutil} | R Documentation |
Simulate Power to Select Best Group by Ranks (Normal Outcomes)
Description
Estimates the empirical power to identify the most promising group as best, using weighted ranks across outcomes, assuming normally distributed outcomes.
Usage
sim_power_best_norm_rank(
noutcomes,
sd,
dif,
weights,
ngroups,
npergroup,
nsim,
conf.level = 0.95
)
Arguments
noutcomes |
Integer. Number of outcomes to evaluate. |
sd |
Numeric vector. Standard deviations for each outcome. |
dif |
Numeric vector. Difference in means between the best and other groups. |
weights |
Numeric vector. Weights per outcome. |
ngroups |
Integer. Number of groups. |
npergroup |
Integer or vector. Number of subjects per group. |
nsim |
Integer. Number of simulations. |
conf.level |
Numeric. Confidence level for the empirical power estimate |
Details
Each outcome is independent and normally distributed. The most promising group
is assumed to have a mean at least dif
higher than the others. Ranks are
weighted and summed per group across outcomes.
If weights
is specified, it is internally scaled to sum to 1.
The most promising group is always considered to be the first group.
Value
An S3 object of class empirical_power_result
, which contains
the estimated empirical power and its confidence interval. The object can
be printed, formatted, or further processed using associated S3 methods.
See also empirical_power_result
.
See Also
Examples
sim_power_best_norm_rank(
noutcomes = 3,
sd = c(1, 0.8, 1.5),
dif = c(0.2, 0.15, 0.3),
weights = c(0.5, 0.3, 0.2),
ngroups = 3,
npergroup = c(30, 25, 25),
nsim = 1000
)