Pairwise two-sample independence tests

Conducts pairwise two-sample independence tests across groups.

pairwisePermutationTest(
  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 stats::p.adjust.

...

Additional arguments passed to coin::independence_test.

Value

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

Details

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

This function is a wrapper for coin::independence_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.

For some options for common tests, see Horthorn et al., 2008.

Note

The parsing of the formula is simplistic. The first variable on the left side is used as the measurement variable. The first variable on the right side is used for the grouping variable.

References

https://rcompanion.org/handbook/K_02.html

Hothorn, T., K. Hornik, M.A. van de Wiel, and A. Zeileis. 2008. Implementing a Class of Permutation Tests: The coin Package. Journal of Statistical Software, 28(8), 1–23.

See also

pairwisePermutationMatrix

Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

Examples

### Fisher-Pitman test

data(BrendonSmall)

library(coin)
                     
independence_test(Sodium ~ Instructor, data = BrendonSmall, 
                 teststat="quadratic")
#> 
#> 	Asymptotic General Independence Test
#> 
#> data:  Sodium by
#> 	 Instructor (Brendon Small, Jason Penopolis, Melissa Robins, Paula Small, Coach McGuirk)
#> chi-squared = 30.34, df = 4, p-value = 4.174e-06
#> 
                                       
PT = pairwisePermutationTest(Sodium ~ Instructor,
                             data   = BrendonSmall,
                             teststat="quadratic",
                             method = "fdr")
PT
#>                              Comparison      Stat   p.value p.adjust
#> 1   Brendon Small - Jason Penopolis = 0     1.475    0.2245 0.249400
#> 2    Brendon Small - Melissa Robins = 0      9.43  0.002135 0.004270
#> 3       Brendon Small - Paula Small = 0     12.34 0.0004433 0.001208
#> 4     Brendon Small - Coach McGuirk = 0     12.34 0.0004439 0.001208
#> 5  Jason Penopolis - Melissa Robins = 0     7.923  0.004881 0.008135
#> 6     Jason Penopolis - Paula Small = 0     12.18 0.0004822 0.001208
#> 7   Jason Penopolis - Coach McGuirk = 0     12.18  0.000483 0.001208
#> 8      Melissa Robins - Paula Small = 0     3.039   0.08129 0.102600
#> 9    Melissa Robins - Coach McGuirk = 0     3.023   0.08209 0.102600
#> 10      Paula Small - Coach McGuirk = 0 0.0002368    0.9877 0.987700

cldList(comparison = PT$Comparison,
        p.value    = PT$p.adjust,
        threshold  = 0.05)
#>            Group Letter MonoLetter
#> 1   BrendonSmall      a         a 
#> 2 JasonPenopolis      a         a 
#> 3  MelissaRobins      b          b
#> 4     PaulaSmall      b          b
#> 5   CoachMcGuirk      b          b