plot.findn: Plot of a findn Object

In findn: Simulation Based Sample Size Estimation

Plot of a findn Object

Description

Plot of a findn Object

Usage

## S3 method for class 'findn'
plot(x, min_n = 1, max_n = NULL, power_lim = 0.95, ...)

Arguments

x	object of class findn.
min_n	lower limit of the x-axis.
max_n	upper limit of the x-axis. The default is NULL.
power_lim	if max_n is NULL then the upper limit of the x-axis is the smallest sample size for which the lower limit of the level percent confidence interval for the predicted power exceeds the value of power_lim. The default is 0.95.
...	Further arguments.

Value

None.

Examples

# Function that simulates the outcomes of a two-sample t-test
ttest <- function(mu1 = 0, mu2 = 1, sd, n, k) {
  sample1 <- matrix(rnorm(n = ceiling(n) * k, mean = mu1, sd = sd),
    ncol = k)
  mean1 <- apply(sample1, 2, mean)
  sd1_hat <- apply(sample1, 2, sd)
  sample2 <- matrix(rnorm(n = ceiling(n) * k, mean = mu2, sd = sd),
    ncol = k)
  mean2 <- apply(sample2, 2, mean)
  sd2_hat <- apply(sample2, 2, sd)
  sd_hat <- sqrt((sd1_hat^2 + sd2_hat^2) / 2)
  teststatistic <- (mean1 - mean2) / (sd_hat * sqrt(2 / n))
  crit <- qt(1 - 0.025, 2*n - 2)
  return(mean(teststatistic < -crit))
}

# Create a findn object
res.ttest <- findn(fun = ttest, targ = 0.8, k = 25, start = 100, 
  init_evals = 100, r = 4, stop = "evals", max_evals = 2000, 
  level = 0.05, var_a = 0.05, var_b = 1, alpha = 0.025, 
  alternative = "one.sided", sd = 2, verbose = FALSE)

# plot with default settings
plot(res.ttest, power_lim = 0.95)

findn documentation built on March 30, 2026, 9:07 a.m.