rcompanion (version 2.4.30)

pairwisePermutationSymmetry: Pairwise two-sample symmetry tests

Description

Conducts pairwise two-sample symmetry tests across groups.

Usage

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

Value

A dataframe of the groups being compared, the p-values, and the adjusted p-values.

Arguments

formula

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

data

The data frame to use.

x

The response variable as a vector.

g

The grouping variable as a vector.

b

The blocking variable as a vector.

method

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

...

Additional arguments passed to coin::symmetry_test.

Author

Salvatore Mangiafico,

Details

The input should include either formula and data; or x, g, and b.

This function is a wrapper for coin::symmetry_test, passing pairwise groups to the function. It's critical to read and understand the documentation for this function to understand its use and options.

References

http://rcompanion.org/handbook/K_03.html

See Also

pairwisePermutationSymmetryMatrix

Examples

data(BobBelcher)

BobBelcher$Instructor = factor( BobBelcher$Instructor, 
                                levels = c("Linda Belcher", "Louise Belcher",
                                           "Tina Belcher", "Bob Belcher",
                                           "Gene Belcher"))
                                           
library(coin)

symmetry_test(Likert ~ Instructor | Rater, data= BobBelcher,
              ytrafo   = rank_trafo,
              teststat = "quadratic")

PT = pairwisePermutationSymmetry(Likert ~ Instructor | Rater,
                                 data     = BobBelcher,
                                 ytrafo   = rank_trafo,
                                 teststat = "quadratic",
                                 method   = "fdr")
PT

cldList(comparison = PT$Comparison,
        p.value    = PT$p.adjust,
       threshold  = 0.05)