Usage
ggcoef_multicomponents(
model,
type = c("dodged", "faceted", "table"),
component_col = "component",
component_label = NULL,
tidy_fun = broom.helpers::tidy_with_broom_or_parameters,
tidy_args = NULL,
conf.int = TRUE,
conf.level = 0.95,
exponentiate = FALSE,
variable_labels = NULL,
term_labels = NULL,
interaction_sep = " * ",
categorical_terms_pattern = "{level}",
add_reference_rows = TRUE,
no_reference_row = NULL,
intercept = FALSE,
include = dplyr::everything(),
significance = 1 - conf.level,
significance_labels = NULL,
return_data = FALSE,
table_stat = c("estimate", "ci", "p.value"),
table_header = NULL,
table_text_size = 3,
table_stat_label = NULL,
ci_pattern = "{conf.low}, {conf.high}",
table_witdhs = c(3, 2),
...
)
ggcoef_multinom(
model,
type = c("dodged", "faceted", "table"),
y.level_label = NULL,
tidy_fun = broom.helpers::tidy_with_broom_or_parameters,
tidy_args = NULL,
conf.int = TRUE,
conf.level = 0.95,
exponentiate = FALSE,
variable_labels = NULL,
term_labels = NULL,
interaction_sep = " * ",
categorical_terms_pattern = "{level}",
add_reference_rows = TRUE,
no_reference_row = NULL,
intercept = FALSE,
include = dplyr::everything(),
significance = 1 - conf.level,
significance_labels = NULL,
return_data = FALSE,
table_stat = c("estimate", "ci", "p.value"),
table_header = NULL,
table_text_size = 3,
table_stat_label = NULL,
ci_pattern = "{conf.low}, {conf.high}",
table_witdhs = c(3, 2),
...
)
Arguments
- model
a regression model object
- type
a dodged plot, a faceted plot or multiple table plots?
- component_col
name of the component column
- component_label
an optional named vector for labeling components
- tidy_fun
(
function
)
Option to specify a custom tidier function.- tidy_args
Additional arguments passed to
broom.helpers::tidy_plus_plus()
and totidy_fun
- conf.int
(
logical
)
Should confidence intervals be computed? (seebroom::tidy()
)- conf.level
the confidence level to use for the confidence interval if
conf.int = TRUE
; must be strictly greater than 0 and less than 1; defaults to 0.95, which corresponds to a 95 percent confidence interval- exponentiate
if
TRUE
a logarithmic scale will be used for x-axis- variable_labels
(
formula-list-selector
)
A named list or a named vector of custom variable labels.- term_labels
(
list
orvector
)
A named list or a named vector of custom term labels.- interaction_sep
(
string
)
Separator for interaction terms.- categorical_terms_pattern
(
glue pattern
)
A glue pattern for labels of categorical terms with treatment or sum contrasts (seemodel_list_terms_levels()
).- add_reference_rows
(
logical
)
Should reference rows be added?- no_reference_row
(
tidy-select
)
Variables for those no reference row should be added, whenadd_reference_rows = TRUE
.- intercept
(
logical
)
Should the intercept(s) be included?- include
(
tidy-select
)
Variables to include. Default iseverything()
. See alsoall_continuous()
,all_categorical()
,all_dichotomous()
andall_interaction()
.- significance
level (between 0 and 1) below which a coefficient is consider to be significantly different from 0 (or 1 if
exponentiate = TRUE
),NULL
for not highlighting such coefficients- significance_labels
optional vector with custom labels for significance variable
- return_data
if
TRUE
, will return the data.frame used for plotting instead of the plot- table_stat
statistics to display in the table, use any column name returned by the tidier or
"ci"
for confidence intervals formatted according toci_pattern
- table_header
optional custom headers for the table
- table_text_size
text size for the table
- table_stat_label
optional named list of labeller functions for the displayed statistic (see examples)
- ci_pattern
glue pattern for confidence intervals in the table
- table_witdhs
relative widths of the forest plot and the coefficients table
- ...
parameters passed to
ggcoef_plot()
- y.level_label
an optional named vector for labeling
y.level
(see examples)