generic.chisq.test: Statistical Power for the Generic Chi-square Test
In pwrss: Statistical Power and Sample Size Calculation Tools

power.chisq

R Documentation

Statistical Power for the Generic Chi-square Test

Description

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

Usage

power.chisq.test(ncp, null.ncp = 0, df, alpha = 0.05,
                 plot = TRUE, verbose = TRUE, pretty = FALSE)

Arguments

`ncp`	non-centrality parameter for the alternative.
`null.ncp`	non-centrality parameter for the null.
`df`	integer; degrees of freedom. For example, for the test of independence df = (nrow - 1)*(ncol - 1).
`alpha`	type 1 error rate, defined as the probability of incorrectly rejecting a true null hypothesis, denoted as `\alpha`.
`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

power

statistical power (1-\beta).

Examples

# power is defined as the probability of observing Chi-square-statistics
# greater than the critical  value
power.chisq.test(ncp = 20, df = 100, alpha = 0.05)

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