jmv: anovaNP – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

anovaNP

One-Way ANOVA (Non-parametric)

Description

The Kruskal-Wallis test is used to explore the relationship between a continuous dependent variable, and a categorical explanatory variable. It is analagous to ANOVA, but with the advantage of being non-parametric and having fewer assumptions. However, it has the limitation that it can only test a single explanatory variable at a time.

Usage

anovaNP(data, deps, group, es = FALSE, pairs = FALSE, formula)

Arguments

`data`	the data as a data frame
`deps`	a string naming the dependent variable in `data`
`group`	a string naming the grouping or independent variable in `data`
`es`	`TRUE` or `FALSE` (default), provide effect-sizes
`pairs`	`TRUE` or `FALSE` (default), perform pairwise comparisons
`formula`	(optional) the formula to use, see the examples

Value

A results object containing:

`results$table`					a table of the test results
`results$comparisons`					an array of pairwise comparison tables

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$table$asDF

as.data.frame(results$table)

Examples

data('ToothGrowth')

anovaNP(formula = len ~ dose, data=ToothGrowth)

#
#  ONE-WAY ANOVA (NON-PARAMETRIC)
#
#  Kruskal-Wallis
#  -------------------------------
#           X²      df    p
#  -------------------------------
#    len    40.7     2    < .001
#  -------------------------------
#

jmv

The 'jamovi' Analyses

v1.2.23

GPL (>= 2)

Authors

Ravi Selker, Jonathon Love, Damian Dropmann

Initial release

2020-06-26