Simulate Power to Select the Best Group Using Binomial Outcomes

Estimates the empirical power to correctly identify the best group as having the highest outcome, under a binomial distribution. Assumes that the most promising group has a higher success probability than the others by at least dif, and that outcomes are independent.

Usage

sim_power_best_binomial(
  noutcomes,
  p1,
  dif,
  ngroups,
  npergroup,
  nsim,
  conf.level = 0.95
)

Arguments

noutcomes: Integer. Number of outcomes to evaluate.
p1: Numeric. Probability in the most promising group (scalar or vector).
dif: Numeric. Difference between the best group and the rest.
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

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.

Details

Multiple outcomes can be evaluated simultaneously. The power is estimated as the proportion of simulations where the most promising group is selected best in all outcomes.

Examples

sim_power_best_binomial(
  noutcomes = 1,
  p1 = 0.7,
  dif = 0.2,
  ngroups = 3,
  npergroup = 30,
  nsim = 1000
)
#> Empirical Power Result
#> ----------------------- 
#> Power:       0.9050
#> 95% CI:      [0.8851, 0.9225]
#> Simulations: 1000