Compact Letter Display of All-Pairwise Comparisons

Adds the compact letter display (CLD) to a pairwise comparison result. Groups that do not share a letter are significantly different. This is a convenient way to annotate plots (e.g. one letter per box/bar) after an all-pairwise post-hoc test such as tukey_hsd(), dunn_test(), games_howell_test(), conover_test(), wilcox_test() or t_test().

The letters are computed with the insert-and-absorb algorithm (Piepho, 2004) using base R only, so no additional package is required (the results match multcompView::multcompLetters()).

Usage

add_cld(test, p.col = NULL, threshold = 0.05, reversed = FALSE, ...)

Arguments

test: an all-pairwise comparison result returned by an rstatix function (e.g. tukey_hsd(), dunn_test(), a pairwise t_test()/wilcox_test(), ...). Must contain the group1 and group2 columns and a p-value column.
p.col: character. The p-value column to threshold. If NULL (default), "p.adj" is used when present, otherwise "p".
threshold: the significance threshold (default 0.05). Comparisons with a p-value below threshold are treated as significant; comparisons with a missing (NA) p-value are treated as non-significant.
reversed: logical. If TRUE, reverses the order in which the letters are assigned (so that, with groups ordered by increasing level, the later groups receive the earlier letters). Default is FALSE.
...: not used.

Value

a tibble with one row per group and the following columns: any grouping variables (for a grouped test), .y. (the outcome variable, when present), group (the group level) and cld (the compact letter display). Groups sharing a letter are not significantly different.

References

Piepho, H.-P. (2004) An Algorithm for a Letter-Based Representation of All-Pairwise Comparisons. Journal of Computational and Graphical Statistics, 13(2), 456-466.

Examples

# Tukey HSD post-hoc, then compact letter display
res <- ToothGrowth %>%
  mutate(dose = factor(dose)) %>%
  tukey_hsd(len ~ dose)
res %>% add_cld()
#> # A tibble: 3 × 3
#>   term  group cld  
#>   <chr> <chr> <chr>
#> 1 dose  0.5   a    
#> 2 dose  1     b    
#> 3 dose  2     c    

# Works on rank-based post-hocs too
ToothGrowth %>% dunn_test(len ~ dose) %>% add_cld()
#> # A tibble: 3 × 3
#>   .y.   group cld  
#>   <chr> <chr> <chr>
#> 1 len   0.5   a    
#> 2 len   1     b    
#> 3 len   2     c    

# Grouped pairwise test -> one CLD per group
ToothGrowth %>%
  mutate(dose = factor(dose)) %>%
  group_by(supp) %>%
  tukey_hsd(len ~ dose) %>%
  add_cld()
#> # A tibble: 6 × 4
#>   supp  term  group cld  
#>   <fct> <chr> <chr> <chr>
#> 1 OJ    dose  0.5   a    
#> 2 OJ    dose  1     b    
#> 3 OJ    dose  2     b    
#> 4 VC    dose  0.5   a    
#> 5 VC    dose  1     b    
#> 6 VC    dose  2     c