lsmeans support for glht

Description

These functions and methods provide an interface between lsmeans and the glht function for simultaneous inference in the multcomp package.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
## S3 method for class 'ref.grid'
as.glht(object, ...)
## S3 method for class 'lsm.list'
as.glht(object, ..., which = 1)

## S3 method for class 'glht.list'
coef(object, ...)
## S3 method for class 'glht.list'
confint(object, ...)
## S3 method for class 'glht.list'
plot(x, ...)
## S3 method for class 'glht.list'
summary(object, ...)
## S3 method for class 'glht.list'
vcov(object, ...)

lsm(...)
pmm(...)

Arguments

object, x

An object of the required class.

which

Numeric index of which element of the lsm.list to use.

...

Additional arguuments to other methods.

Details

lsm (and pmm, which is identical) are meant to be called only from "glht" as its second (linfct) argument. It works similarly to mcp except with specs (and optionally by and contr arguments) provided as in a call to lsmeans or pmmeans.

When there is a non-NULL by variable (either explicitly or implicitly), each “by” group is passed separately to glht and returned as a list of "glht" objects. For convenience, this is classed as "glht.list", and appropriate methods coef, confint, plot, summary, and vcov are provided.

Value

as.glht returns an object of class glht, or of class glht.list if by is non-NULL. The latter is simply a list of glht objects, and the provided methods coef, confint, plot, summary, and vcov simply lapply the corresponding methods for class "glht".

Note

There is also a glht method for class ref.grid, but it is far preferable to use as.glht instead, as its model argument is redundant.

Author(s)

Russell V. Lenth

See Also

lsmeans, glht

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
require(lsmeans)
require(multcomp)

warp.lm <- lm(breaks ~ wool*tension, data = warpbreaks)

# Using 'lsm'
summary(glht(warp.lm, lsm(pairwise ~ tension | wool)))

# Same, but using an existing 'lsmeans' result
warp.lsmobj <- lsmeans(warp.lm, ~ tension | wool)
summary(as.glht(pairs(warp.lsmobj)))

# Same contrasts, but treat as one family
summary(as.glht(pairs(warp.lsmobj), by = NULL))