Add pairwise contrasts for categorical variables
Source: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")
.
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
(
data.frame
)
A tidy tibble as produced bytidy_*()
functions.- variables
include (
tidy-select
)
Variables for those pairwise contrasts should be added. Default isall_categorical()
.- keep_model_terms
(
logical
)
Keep terms from the model?- pairwise_reverse
(
logical
)
Determines whether to use"pairwise"
(ifTRUE
) or"revpairwise"
(ifFALSE
), seeemmeans::contrast()
.- contrasts_adjust
(
string
)
Optional adjustment method when computing contrasts, seeemmeans::contrast()
(ifNULL
, useemmeans
default).- conf.level
(
numeric
)
Confidence level, by default use the value indicated previously intidy_and_attach()
.- emmeans_args
(
list
)
List of additional parameter to pass toemmeans::emmeans()
when computing pairwise contrasts.- model
(a model object, e.g.
glm
)
The corresponding model, if not attached tox
.- quiet
(
logical
)
Whetherbroom.helpers
should not return a message when requested output cannot be generated. Default isFALSE
.
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 (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()
}
}
}