tidy_add_pairwise_contrasts {broom.helpers} | R Documentation |
Add pairwise contrasts for categorical variables
Description
Computes pairwise contrasts with emmeans::emmeans()
and add them to the
results tibble. Works only with models supported by emmeans
, see
vignette("models", package = "emmeans")
.
Usage
tidy_add_pairwise_contrasts(
x,
variables = all_categorical(),
keep_model_terms = FALSE,
pairwise_reverse = TRUE,
contrasts_adjust = NULL,
conf.level = attr(x, "conf.level"),
emmeans_args = list(),
model = tidy_get_model(x),
quiet = FALSE
)
Arguments
x |
a tidy tibble |
variables |
a vector indicating the name of variables
for those pairwise contrasts should be added.
Accepts tidyselect syntax. Default is |
keep_model_terms |
keep terms from the model? |
pairwise_reverse |
determines whether to use |
contrasts_adjust |
optional adjustment method when computing contrasts,
see |
conf.level |
confidence level, by default use the value indicated
previously in |
emmeans_args |
list of additional parameter to pass to
|
model |
the corresponding model, if not attached to |
quiet |
logical argument whether broom.helpers should not return
a message when requested output cannot be generated. Default is |
Note
If the contrasts
column is not yet available in x
,
tidy_add_contrasts()
will be automatically applied.
For multi-components models, such as zero-inflated Poisson or beta regression, support of pairwise contrasts is still experimental.
See Also
Other tidy_helpers:
tidy_add_coefficients_type()
,
tidy_add_contrasts()
,
tidy_add_estimate_to_reference_rows()
,
tidy_add_header_rows()
,
tidy_add_n()
,
tidy_add_reference_rows()
,
tidy_add_term_labels()
,
tidy_add_variable_labels()
,
tidy_attach_model()
,
tidy_disambiguate_terms()
,
tidy_identify_variables()
,
tidy_plus_plus()
,
tidy_remove_intercept()
,
tidy_select_variables()
Examples
if (.assert_package("emmeans", boolean = TRUE)) {
mod1 <- lm(Sepal.Length ~ Species, data = iris)
mod1 %>%
tidy_and_attach() %>%
tidy_add_pairwise_contrasts()
mod1 %>%
tidy_and_attach() %>%
tidy_add_pairwise_contrasts(pairwise_reverse = FALSE)
mod1 %>%
tidy_and_attach() %>%
tidy_add_pairwise_contrasts(keep_model_terms = TRUE)
mod1 %>%
tidy_and_attach() %>%
tidy_add_pairwise_contrasts(contrasts_adjust = "none")
if (.assert_package("gtsummary", boolean = TRUE)) {
mod2 <- glm(
response ~ age + trt + grade,
data = gtsummary::trial,
family = binomial
)
mod2 %>%
tidy_and_attach(exponentiate = TRUE) %>%
tidy_add_pairwise_contrasts()
}
}