compute_power {boodd} | R Documentation |
Compute the Power of a Statistical Test
Description
This function computes the power of a statistical test given the distributions under the null and alternative hypotheses for a specified significance level.
Usage
compute_power(null_dist, alt_dist, alpha)
Arguments
null_dist |
A numeric vector representing the distribution under the null hypothesis. |
alt_dist |
A numeric vector representing the distribution under an alternative hypothesis. |
alpha |
A numeric value in |
Details
The function calculates the proportion of values of the alternative
distribution that falls into the critical region determined by the distribution
under the null for an error rate alpha
.
Value
A numeric value estimating the power of the test.
References
Bertail, P. and Dudek, A. (2025). Bootstrap for Dependent Data, with an R package (by Bernard Desgraupes and Karolina Marek) - submitted.
Beran, R. (1986). Simulated Power Functions. The Annals of Statistics, 14, 151-173.
See Also
Examples
# Generate two normally distributed samples as null and alternative distributions
set.seed(123)
null_dist <- rnorm(1000, mean = 0, sd = 1) # Null distribution
alt_dist <- rnorm(1000, mean = 0.5, sd = 1) # Alternative distribution
alpha <- 0.05 # Significance level
# Compute the power of the test
test_power <- compute_power(null_dist, alt_dist, alpha)
print(test_power)