The rmanova
function computes a one-way repeated measures ANOVA for the trimmed means. Homoscedasticity assumption not required.
Corresponding post hoc tests can be performed using rmmcp
.
rmanova(y, groups, blocks, tr = 0.2)
rmmcp(y, groups, blocks, tr = 0.2)
a numeric vector of data values (response).
a vector giving the group of the corresponding elements of y.
a vector giving the block of the corresponding elements of y.
trim level for the mean.
rmanova
an object of class "t1way"
containing:
value of the test statistic
degrees of freedom
degrees of freedom
p-value
function call
rmmcp returns an object of class "mcp1" containing:
inference for all pairwise comparisons
names of the factor levels
Wilcox, R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Elsevier.
# NOT RUN {
head(WineTasting)
rmanova(WineTasting$Taste, WineTasting$Wine, WineTasting$Taster)
## post hoc
rmmcp(WineTasting$Taste, WineTasting$Wine, WineTasting$Taster)
head(bush)
require(reshape)
bushLong <- melt(bush, id.var = "participant", variable_name = "food")
rmanova(bushLong$value, bushLong$food, bushLong$participant)
## post hoc
rmmcp(bushLong$value, bushLong$food, bushLong$participant)
# }
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