p_shapiro.test: p-value from Shapiro-Wilk Normality Test simulation

In Spower: Power Analyses using Monte Carlo Simulations

p-value from Shapiro-Wilk Normality Test simulation

Description

Generates univariate distributional data and returns a p-value to assess the null that the population follows a Gaussian distribution shape. Uses shapiro.test.

Usage

p_shapiro.test(dist, return_analysis = FALSE)

Arguments

dist	expression used to generate the required sample data
return_analysis	logical; return the analysis object for further extraction and customization?

Value

a single p-value

Author(s)

Phil Chalmers [e-mail]

Examples

# 50 observations drawn from normal distribution (null is true)
p_shapiro.test(rnorm(50))

# return analysis object
p_shapiro.test(rnorm(50), TRUE)

# 50 observations from slightly skewed chi-squared distribution (power)
p_shapiro.test(rchisq(50, df=100))


    # empirical Type I error rate estimate
    p_shapiro.test(rnorm(50)) |> Spower()

    # power
    p_shapiro.test(rchisq(50, df=100)) |> Spower()

Spower documentation built on Nov. 28, 2025, 1:06 a.m.