rcompanion (version 1.13.2)

pairwiseOrdinalMatrix: Pairwise two-sample ordinal regression with matrix output

Description

Performs pairwise two-sample ordinal regression across groups.

Usage

pairwiseOrdinalMatrix(formula = NULL, data = NULL, x = NULL, g = NULL,
  method = "fdr", ...)

Arguments

formula

A formula indicating the measurement variable and the grouping variable. e.g. y ~ group.

data

The data frame to use.

x

The response variable as a vector.

g

The grouping variable as a vector.

method

The p-value adjustment method to use for multiple tests. See p.adjust.

...

Additional arguments passed to clm.

Value

A list consisting of: A matrix of p-values; the p-value adjustment method; a matrix of adjusted p-values.

Details

Ordinal regression is analogous to general linear regression or generalized linear regression for cases where the dependent variable is an ordinal variable. The ordinal package provides a flexible and powerful implementation of ordinal regression.

The pairwiseOrdinalMatrix function can be used as a post-hoc method following an omnibus ordinal regession whose form is analogous to a one-way analysis of variance. The matrix output can be converted to a compact letter display.

The x variable must be an ordered factor.

References

http://rcompanion.org/handbook/G_07.html

See Also

pairwiseOrdinalTest

Examples

# NOT RUN {
data(PoohPiglet)
PoohPiglet$Likert.f = factor(PoohPiglet$Likert, ordered = TRUE)
PoohPiglet$Speaker = factor(PoohPiglet$Speaker,
                     levels = c("Pooh", "Tigger", "Piglet"))       
PT = pairwiseOrdinalMatrix(Likert.f ~ Speaker,
                           data   = PoohPiglet,
                           method = "fdr")$Adjusted
PT                          
library(multcompView)
multcompLetters(PT,
                compare="<",
                threshold=0.05,
                Letters=letters)
                 
# }