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