sim_power_best_binomial: Simulate Power to Select the Best Group Using Binomial Outcomes

Description

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
)

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.

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

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

Run this code

sim_power_best_binomial(
  noutcomes = 1,
  p1 = 0.7,
  dif = 0.2,
  ngroups = 3,
  npergroup = 30,
  nsim = 1000
)