rcompanion (version 2.4.30)

pairwiseOrdinalIndependence: Pairwise tests of independence for tables with one ordered nominal variable

Description

Conducts pairwise tests for a 2-dimensional table, in which one variable is ordered nominal and one variable is non-ordered nominal. The function relies on the coin package.

Usage

pairwiseOrdinalIndependence(
  x,
  compare = "row",
  scores = NULL,
  method = "fdr",
  digits = 3,
  ...
)

Value

A data frame of comparisons, p-values, and adjusted p-values.

Arguments

x

A two-way contingency table. One dimension is ordered and one is non-ordered nominal.

compare

If "row", treats the rows as the grouping variable. If "column", treats the columns as the grouping variable.

scores

Optional vector to specify the spacing of the ordered variable.

method

The method to adjust multiple p-values. See stats::p.adjust.

digits

The number of significant digits in the output.

...

Additional arguments, passed to stats::chisq_test.

Author

Salvatore Mangiafico,

References

http://rcompanion.org/handbook/H_09.html

See Also

pairwiseNominalIndependence

Examples

### Independence test for table with one ordered variable
data(Breakfast)
require(coin)
chisq_test(Breakfast,
           scores = list("Breakfast" = c(-2, -1, 0, 1, 2)))
PT = pairwiseOrdinalIndependence(Breakfast, compare = "row")
PT
cldList(comparison = PT$Comparison, 
        p.value    = PT$p.value, 
        threshold  = 0.05)
        
### Similar to Kruskal-Wallis test for Likert data
data(PoohPiglet)
XT = xtabs(~ Speaker + Likert, data = PoohPiglet)
XT
require(coin)
chisq_test(XT,
           scores = list("Likert" = c(1, 2, 3, 4, 5)))
PT=pairwiseOrdinalIndependence(XT, compare = "row")
PT
cldList(comparison = PT$Comparison, 
        p.value    = PT$p.value, 
        threshold  = 0.05)