par.2aov: Parametric/non parametric test evaluation for multivariate...

In mmiots9/miotsdata: Miotsdata

Description

Get info about normality and variances of the given vectors in ordere to decide wether use 2-way ANOVA or Kruskal-Wallis

Usage

mrt.par.2aov(x, y, z, type.of.int = "+")

Arguments

x	Numeric vector (or dataframe column)
y	A vector of factors
z	A vector of factors
tyoe.of.int	"+" to compute the analysis on the two categorial variables only or "*" to compute also the analysis on the interaction

Value

Shapiro categorie	A dataframe containing W and p-value coming from shapiro.test of x in the two different categoric conditions
Bartlett	A dataframe containing k-squared value, df and p-value coming from bartlett.test of x in the two different categoric conditions and, if type.of.int = "*", also from the interaction of the two categorical
Shapiro interazione	optional, only if type.of.int = "*". Return the W and p-value coming from the shapiro test of all the possible interaction of y and z over x

Author(s)

Matteo Miotto

Examples

par.2aov(rnorm(100), sample(rep(c(0,1), 50)), sample(rep(c("a", "b", "c", "d"), 25)), type.of.int = "*")

mmiots9/miotsdata documentation built on Dec. 21, 2021, 8:06 p.m.