Compact letter displays

A method for multcomp::cld() is provided for users desiring to produce compact-letter displays (CLDs). This method uses the Piepho (2004) algorithm (as implemented in the multcompView package) to generate a compact letter display of all pairwise comparisons of estimated marginal means. The function obtains (possibly adjusted) P values for all pairwise comparisons of means, using the contrast function with method = "pairwise". When a P value exceeds alpha, then the two means have at least one letter in common.

Usage

# S3 method for emmGrid
cld(object, details = FALSE, sort = TRUE, by,
  alpha = 0.05, Letters = c("1234567890", LETTERS, letters),
  reversed = decreasing, decreasing = FALSE, signif.sets = FALSE,
  delta = 0, ...)

# S3 method for emm_list
cld(object, ..., which = 1)

Arguments

object

An object of class emmGrid

details

Logical value determining whether detailed information on tests of pairwise comparisons is displayed

sort

Logical value determining whether the EMMs are sorted before the comparisons are produced. When TRUE, the results are displayed according to reversed.

by

Character value giving the name or names of variables by which separate families of comparisons are tested. If NULL, all means are compared. If missing, the object's by.vars setting, if any, is used.

alpha

Numeric value giving the significance level for the comparisons

Letters

Character vector of letters to use in the display. Any strings of length greater than 1 are expanded into individual characters

reversed, decreasing

Logical value (passed to multcompView::multcompLetters.) If TRUE, the order of use of the letters is reversed. Either reversed or decreasing may be specified, thus providing compatibility with both multcompView::multcompLetters(..., reversed, ...) and multcomp::cld(..., decreasing, ...). In addition, if both sort and reversed are TRUE, the sort order of results is reversed.

signif.sets

Logical value. If FALSE (and delta = 0), a ‘traditional’ compact-letter display is constructed with groupings representing sets of estimates that are not statistically different. If TRUE, the criteria are reversed so that two estimates sharing the same symbol test as significantly different. See also delta.

delta

Numeric value passed to test.emmGrid. If this is positive, it is used as an equivalence threshold in the TOST procedure for two-sided equivalence testing. In the resulting compact letter display, two estimates share the same grouping letter only if they are found to be statistically equivalent -- that is, groupings reflect actual findings of equivalence rather than failure to find a significant difference. When delta is nonzero, signif.sets is ignored.

...

Arguments passed to contrast (for example, an adjust method)

which

Which element of the emm_list object to process (If length exceeds one, only the first one is used)

Value

A summary_emm object showing the estimated marginal means plus an additional column labeled .group (when signif.sets = FALSE), .signif.set (when signif.sets = TRUE), or .equiv.set

(when delta > 0).

Note

We warn that the default display encourages a poor practice in interpreting significance tests. Such CLDs are misleading because they visually group means with comparisons P > alpha as though they are equal, when in fact we have only failed to prove that they differ. A better alternative if one wants to show groupings is to specify an equivalence threshold delta; then groupings will be based on actual findings of equivalence. Another way to display actual findings is to set signif.sets = TRUE, so that estimates in the same group are those found to be statistically different. Obviously, these different options require different interpretations of the results; the annotations and the label given the final column help guide how to assess the results.

As further alternatives, consider pwpp (graphical display of P values) or pwpm (matrix display).

References

Piepho, Hans-Peter (2004) An algorithm for a letter-based representation of all pairwise comparisons, Journal of Computational and Graphical Statistics, 13(2), 456-466.

Examples

if(requireNamespace("multcomp"))
    emm_example("cld-multcomp")
#> 
#> --- Running code from 'system.file("extexamples", "cld-multcomp.R", package = "emmeans")'
#> 
#> > pigs.lm <- lm(log(conc) ~ source + factor(percent), 
#> +     data = pigs)
#> 
#> > pigs.emm <- emmeans(pigs.lm, "percent", type = "response")
#> 
#> > multcomp::cld(pigs.emm, alpha = 0.1, Letters = LETTERS)
#>  percent response   SE df lower.CL upper.CL .group
#>        9     31.4 1.28 23     28.8     34.1  A    
#>       12     37.5 1.44 23     34.7     40.6   B   
#>       15     39.0 1.70 23     35.6     42.7   B   
#>       18     42.3 2.24 23     37.9     47.2   B   
#> 
#> Results are averaged over the levels of: source 
#> Confidence level used: 0.95 
#> Intervals are back-transformed from the log scale 
#> P value adjustment: tukey method for comparing a family of 4 estimates 
#> Tests are performed on the log scale 
#> significance level used: alpha = 0.1 
#> NOTE: If two or more means share the same grouping symbol,
#>       then we cannot show them to be different.
#>       But we also did not show them to be the same. 
#> 
#> > multcomp::cld(pigs.emm, alpha = 0.1, signif.sets = TRUE)
#>  percent response   SE df lower.CL upper.CL .signif.set
#>        9     31.4 1.28 23     28.8     34.1  123       
#>       12     37.5 1.44 23     34.7     40.6  1         
#>       15     39.0 1.70 23     35.6     42.7   2        
#>       18     42.3 2.24 23     37.9     47.2    3       
#> 
#> Results are averaged over the levels of: source 
#> Confidence level used: 0.95 
#> Intervals are back-transformed from the log scale 
#> P value adjustment: tukey method for comparing a family of 4 estimates 
#> Tests are performed on the log scale 
#> significance level used: alpha = 0.1 
#> Estimates sharing the same symbol are significantly different 
#> 
#> > multcomp::cld(pigs.emm, delta = log(1.25), adjust = "sidak")
#>  percent response   SE df lower.CL upper.CL .equiv.set
#>        9     31.4 1.28 23     28.1     35.0  1        
#>       12     37.5 1.44 23     33.8     41.6   2       
#>       15     39.0 1.70 23     34.6     43.9   2       
#>       18     42.3 2.24 23     36.7     48.8    3      
#> 
#> Results are averaged over the levels of: source 
#> Confidence level used: 0.95 
#> Conf-level adjustment: sidak method for 4 estimates 
#> Intervals are back-transformed from the log scale 
#> P value adjustment: sidak method for 6 tests 
#> Statistics are tests of equivalence with a threshold of 0.22314 
#> P values are left-tailed 
#> Tests are performed on the log scale 
#> significance level used: alpha = 0.05 
#> Estimates sharing the same symbol test as equivalent 
#> 
    # Use emm_example("cld-multcomp", list = TRUE) # to just list the code