nca_power {NCA} | R Documentation |
Function to evaluate power
Description
Function to evaluate power, test if a sample size is large enough to detect necessity.
Usage
nca_power(n = c(20, 50, 100), effect = 0.10, slope = 1, ceiling = "ce_fdh",
p = 0.05, distribution.x = "uniform", distribution.y = "uniform", rep = 100,
test.rep = 200)
Arguments
n |
Number of datapoints to generate, either an integer or a vector of integers. |
effect |
Effect size of the generated datasets. |
slope |
Slope of the line. |
ceiling |
Ceiling technique to use for this analysis |
p |
Targeted confidence level |
distribution.x |
Distribution type(s) for X, "uniform" (default) or "normal". |
distribution.y |
Distribution type(s) for Y, "uniform" (default) or "normal". |
rep |
Number of analyses done per iteration. |
test.rep |
Number of resamples in the statistical approximate permutation test. For test.rep = 0 no statistical test is performed |
Examples
# Simple example
## Not run: results <- nca_power()
print(results)
[Package NCA version 4.0.1 Index]