anovaRMNP {jmv}

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
#  ------------------------
#