generic.binom.test: Power Analysis for the Generic Binomial Test

In pwrss: Statistical Power and Sample Size Calculation Tools

Power Analysis for the Generic Binomial Test

Description

Calculates power for the generic binomial test with (optional) Type 1 and Type 2 error plots.

Usage

power.binom.test(size, prob, null.prob = 0.5, alpha = 0.05,
                 alternative = c("two.sided", "one.sided", "two.one.sided"),
                 plot = TRUE, verbose = TRUE, pretty = FALSE)

Arguments

size	number of trials (zero or more).
prob	probability of success on each trial under alternative.
null.prob	probability of success on each trial under null.
alpha	type 1 error rate, defined as the probability of incorrectly rejecting a true null hypothesis, denoted as \alpha.
alternative	direction or type of the hypothesis test: "two.sided", "one.sided", or "two.one.sided". For non-inferiority or superiority tests, add or subtract the margin from the null hypothesis value and use alternative = "one.sided".
plot	logical; FALSE switches off Type 1 and Type 2 error plot. TRUE by default.
verbose	logical; whether the output should be printed on the console. TRUE by default.
pretty	logical; whether the output should show Unicode characters (if encoding allows for it). FALSE by default.

Value

size	number of trials (zero or more).
prob	probability of success on each trial under alternative.
null.prob	probability of success on each trial under null.
binom.alpha	critical value(s).
power	statistical power (1-\beta).

Examples

# one-sided
power.binom.test(size = 200, prob = 0.6, null.prob = 0.5,
                 alpha = 0.05, alternative = "one.sided")

# two-sided
power.binom.test(size = 200, prob = 0.4, null.prob = 0.5,
                 alpha = 0.05, alternative = "two.sided")

# equivalence
power.binom.test(size = 200, prob = 0.5, null.prob = c(0.4, 0.6),
                 alpha = 0.05, alternative = "two.one.sided")

pwrss documentation built on Sept. 16, 2025, 9:11 a.m.