rmanova: A heteroscedastic one-way repeated measures ANOVA for trimmed...

In WRS2: A Collection of Robust Statistical Methods

A heteroscedastic one-way repeated measures ANOVA for trimmed means.

Description

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.

Usage

rmanova(y, groups, blocks, tr = 0.2, ...)
rmmcp(y, groups, blocks, tr = 0.2, alpha = 0.05, ...)

Arguments

y	a numeric vector of data values (response).
groups	a vector giving the group of the corresponding elements of y.
blocks	a vector giving the block of the corresponding elements of y.
tr	trim level for the mean.
alpha	alpha level for post hoc comparisons.
...	currently ignored.

Value

rmanova an object of class "t1way" containing:

test	value of the test statistic
df1	degrees of freedom
df2	degrees of freedom
p.value	p-value
call	function call

rmmcp returns an object of class "mcp1" containing:

comp	inference for all pairwise comparisons
fnames	names of the factor levels

References

Wilcox, R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Elsevier.

See Also

rmanovab, med1way, t1way

Examples

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)

WRS2 documentation built on Nov. 2, 2023, 6:25 p.m.