cld {lsmeans} | R Documentation |
Extract and display information on all pairwise comparisons of least-squares means.
## S3 method for class 'ref.grid' cld(object, details = FALSE, sort = TRUE, by, alpha = 0.05, Letters = c("1234567890", LETTERS, letters), ...) ## S3 method for class 'lsm.list' cld(object, ..., which = 1)
object |
An object of class |
details |
Logical value determining whether detailed information on tests of pairwise comparisons is displayed |
sort |
Logical value determining whether the LS means are sorted before the comparisons are produced |
by |
Character value giving the name or names of variables by which separate
families of comparisons are tested.
If |
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 |
... |
Arguments passed to |
which |
When |
This function uses the Piepho (2004) algorithm (as implemented in the multcompView package) to generate a compact letter display of all pairwise comparisons of least-squares 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.
When details == FALSE
, an object of class summary.ref.grid
(which inherits from data.frame
) showing the summary of LS means with an added column named .groups
with the cld information. When details == TRUE
, a list the object just described, as well as the summary of the contrast
results showing each comparison, its estimate, standard error, t ratio, and adjusted P value.
This function requires the multcompView package to be installed. Otherwise an error message is produced.
Russell V. Lenth
Hans-Peter Piepho (2004) An algorithm for a letter-based representation of all pairwise comparisons, Journal of Computational and Graphical Statistics, 13(2), 456-466.
cld
in the multcomp package
warp.lm <- lm(breaks ~ wool * tension, data = warpbreaks) warp.lsm <- lsmeans(warp.lm, ~ tension | wool) cld(warp.lsm) # implicitly uses by = "wool" cld(warp.lsm, by = "tension") # overrides implicit 'by' # Mimic grouping bars and compare all 6 means cld(warp.lsm, by = NULL, Letters = "||||||||", alpha = .01)