R/tidy_add_pairwise_contrasts.R
tidy_add_pairwise_contrasts.Rd
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")
.
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
)
a tidy tibble
a vector indicating the name of variables
for those pairwise contrasts should be added.
Accepts tidyselect syntax. Default is all_categorical()
keep terms from the model?
determines whether to use "pairwise"
(if TRUE
)
or "revpairwise"
(if FALSE
), see emmeans::contrast()
optional adjustment method when computing contrasts,
see emmeans::contrast()
(if NULL
, use emmeans
default)
confidence level, by default use the value indicated
previously in tidy_and_attach()
list of additional parameter to pass to
emmeans::emmeans()
when computing pairwise contrasts
the corresponding model, if not attached to x
logical argument whether broom.helpers should not return
a message when requested output cannot be generated. Default is FALSE
If the contrasts
column is not yet available in x
,
tidy_add_contrasts()
will be automatically applied.
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()
if (FALSE) { # interactive()
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()
}
}
}