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",
corner = 1, 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 (single value or vector of values).
slope	Slope of the line (single value or vector of values).
ceiling	Ceiling technique to use for this analysis (single value or vector of values).
corner	Integer, indicating the corner to analyze, see nca_analysis.
p	Significance level.
distribution.x	Distribution type(s) for X, "uniform" (default) or "normal" (single value or vector of values).
distribution.y	Distribution type(s) for Y, "uniform" (default) or "normal" (single value or vector of values).
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. See nca_analysis for reproducible outputs.

Examples

# Simple example
## Not run: results <- nca_power()

print(results)

NCA documentation built on March 20, 2026, 5:08 p.m.