emmip {emmeans} | R Documentation |
Creates an interaction plot of EMMs based on a fitted model and a simple formula specification.
emmip(object, formula, ...) ## Default S3 method: emmip(object, formula, type, CIs = FALSE, engine = get_emm_option("graphics.engine"), pch = c(1, 2, 6, 7, 9, 10, 15:20), lty = 1, col = NULL, plotit = TRUE, ...)
object |
An object of class |
formula |
Formula of the form
|
... |
Additional arguments passed to |
type |
As in |
CIs |
Logical value. If |
engine |
Character value matching |
pch |
The plotting characters to use for each group (i.e., levels of
|
lty |
The line types to use for each group. Recycled as needed. |
col |
The colors to use for each group, recycled as needed. If not specified, the default trellis colors are used. |
plotit |
Logical value. If |
If plotit = FALSE
, a data.frame
(actually, a
summary_emm
object) with the table of EMMs that would be plotted.
The variables plotted are named xvar
and yvar
, and the trace
factor is named tvar
. This data frame has an added "labs"
attribute containing the labels xlab
, ylab
, and tlab
for these respective variables. The confidence limits are also
included, renamed LCL
and UCL
.
If plotit = TRUE
, the function
returns an object of class "ggplot"
or a "trellis"
, depending
on engine
.
If object
is a fitted model, emmeans
is called with an
appropriate specification to obtain estimated marginal means for each
combination of the factors present in formula
(in addition, any
arguments in ...
that match at
, trend
,
cov.reduce
, or fac.reduce
are passed to emmeans
).
Otherwise, if object
is an emmGrid
object, its first element is
used, and it must contain one estimate for each combination of the factors
present in formula
.
Conceptually, this function is equivalent to
interaction.plot
where the summarization function is thought
to return the EMMs.
#--- Three-factor example noise.lm = lm(noise ~ size * type * side, data = auto.noise) # Separate interaction plots of size by type, for each side emmip(noise.lm, type ~ size | side) # One interaction plot, using combinations of size and side as the x factor # ... with added confidence intervals emmip(noise.lm, type ~ side * size, CIs = TRUE) # One interaction plot using combinations of type and side as the trace factor emmip(noise.lm, type * side ~ size) # Individual traces in panels emmip(noise.lm, ~ size | type * side)