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[Deprecated]

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 to tidy_fun

conf.int

(logical)
Should confidence intervals be computed? (see broom::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 or vector)
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 (see model_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, when add_reference_rows = TRUE.

intercept

(logical)
Should the intercept(s) be included?

include

(tidy-select)
Variables to include. Default is everything(). See also all_continuous(), all_categorical(), all_dichotomous() and all_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 to ci_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)