jmv: anovaRMNP – R documentation

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anovaRMNP

Repeated Measures ANOVA (Non-parametric)

Description

The Friedman test is used to explore the relationship between a continuous dependent variable and a categorical explanatory variable, where the explanatory variable is 'within subjects' (where multiple measurements are from the same subject). It is analagous to Repeated Measures ANOVA, but with the advantage of being non-parametric, and not requiring the assumptions of normality or homogeneity of variances. However, it has the limitation that it can only test a single explanatory variable at a time.

Usage

anovaRMNP(
  data,
  measures,
  pairs = FALSE,
  desc = FALSE,
  plots = FALSE,
  plotType = "means"
)

Arguments

`data`	the data as a data frame
`measures`	a vector of strings naming the repeated measures variables
`pairs`	`TRUE` or `FALSE` (default), perform pairwise comparisons
`desc`	`TRUE` or `FALSE` (default), provide descriptive statistics
`plots`	`TRUE` or `FALSE` (default), provide a descriptive plot
`plotType`	`'means'` (default) or `'medians'`, the error bars to use in the plot

Value

A results object containing:

`results$table`					a table of the Friedman test results
`results$comp`					a table of the pairwise comparisons
`results$desc`					a table containing the descriptives
`results$plot`					a descriptives plot

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('bugs', package = 'jmv')

anovaRMNP(bugs, measures = vars(LDLF, LDHF, HDLF, HDHF))

#
#  REPEATED MEASURES ANOVA (NON-PARAMETRIC)
#
#  Friedman
#  ------------------------
#    X²      df    p
#  ------------------------
#    55.8     3    < .001
#  ------------------------
#

jmv

The 'jamovi' Analyses

v1.2.23

GPL (>= 2)

Authors

Ravi Selker, Jonathon Love, Damian Dropmann

Initial release

2020-06-26