assumption.check: assumption.check

In bayesanova: Bayesian Inference in the Analysis of Variance via Markov Chain Monte Carlo in Gaussian Mixture Models

Description

This function checks the assumption of normality for each of the groups x1, x2, x3 (and optional x4, x5 and 6) used in the Bayesian ANOVA via Shapiro-Wilk tests with confidence level conf.level.

Usage

assumption.check(x1,x2,x3,x4=NULL,x5=NULL,x6=NULL,conf.level=0.95)

Arguments

x1	Numerical vector containing the values for the first group
x2	Numerical vector containing the values for the second group
x3	Numerical vector containing the values for the third group
x4	Numerical vector containing the values for the fourth group. Defaults to NULL.
x5	Numerical vector containing the values for the fifth group. Defaults to NULL.
x6	Numerical vector containing the values for the sixth group. Defaults to NULL.
conf.level	Confidence level of the Shapiro-Wilk test used. Significance level equals 1-conf.level

Details

If a single Shapiro-Wilk test fails, the method returns a warning and recommends to use further diagnostics.

Value

Histograms and Quantile-Quantile plots for all groups are produced, either a warning or a confirmation of normality in all three groups is printed to the console.

Author(s)

Riko Kelter

References

For details, see: https://arxiv.org/abs/1906.07524v1

Examples

set.seed(42)
x1=rnorm(75,0,1)
x2=rnorm(75,1,1)
x3=rnorm(75,2,1)

assumption.check(x1,x2,x3,conf.level = 0.95)

bayesanova documentation built on July 2, 2020, 2:29 a.m.