| display.estimate_contrasts | R Documentation |
print() method for modelbased objects. Can be used to tweak the output
of tables.
## S3 method for class 'estimate_contrasts'
display(
object,
select = NULL,
include_grid = NULL,
full_labels = NULL,
format = "markdown",
...
)
## S3 method for class 'estimate_contrasts'
print(x, select = NULL, include_grid = NULL, full_labels = NULL, ...)
select |
Determines which columns are printed and the table layout. There are two options for this argument:
Using Note: glue-like syntax is still experimental in the case of more complex models (like mixed models) and may not return expected results. |
include_grid |
Logical, if |
full_labels |
Logical, if |
format |
String, indicating the output format. Can be |
... |
Arguments passed to |
x, object |
An object returned by the different |
Invisibly returns x.
Columns and table layout can be customized using options():
modelbased_select: options(modelbased_select = <string>) will set a
default value for the select argument and can be used to define a custom
default layout for printing.
modelbased_include_grid: options(modelbased_include_grid = TRUE) will
set a default value for the include_grid argument and can be used to
include data grids in the output by default or not.
modelbased_full_labels: options(modelbased_full_labels = FALSE) will
remove redundant (duplicated) labels from rows.
easystats_display_format: options(easystats_display_format = <value>)
will set the default format for the display() methods. Can be one of
"markdown", "html", or "tt".
Use print_html() and print_md() to create tables in HTML or
markdown format, respectively.
model <- lm(Petal.Length ~ Species, data = iris)
out <- estimate_means(model, "Species")
# default
print(out)
# smaller set of columns
print(out, select = "minimal")
# remove redundant labels
data(efc, package = "modelbased")
efc <- datawizard::to_factor(efc, c("c161sex", "c172code", "e16sex"))
levels(efc$c172code) <- c("low", "mid", "high")
fit <- lm(neg_c_7 ~ c161sex * c172code * e16sex, data = efc)
out <- estimate_means(fit, c("c161sex", "c172code", "e16sex"))
print(out, full_labels = FALSE, select = "{estimate} ({se})")
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