nca_power: Function to evaluate power

In NCA: Necessary Condition Analysis

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)

NCA documentation built on May 29, 2024, 8:47 a.m.