Add references rows for categorical variables
For categorical variables with a treatment contrast
(stats::contr.treatment()
), a SAS contrast (stats::contr.SAS()
)
or a sum contrast (stats::contr.sum()
), add a reference row.
tidy_add_reference_rows( x, no_reference_row = NULL, model = tidy_get_model(x), quiet = FALSE )
x |
a tidy tibble |
no_reference_row |
a vector indicating the name of variables
for those no reference row should be added.
Accepts tidyselect syntax. Default is |
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 FALSE |
The added reference_row
column will be equal to:
TRUE
for a reference row;
FALSE
for a normal row of a variable with a reference row;
NA
for variables without a reference row.
If the contrasts
column is not yet available in x
,
tidy_add_contrasts()
will be automatically applied.
tidy_add_reference_rows()
will not populate the label
of the reference term. It is therefore better to apply
tidy_add_term_labels()
after tidy_add_reference_rows()
rather than before. Similarly, it is better to apply
tidy_add_reference_rows()
before tidy_add_n()
.
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_term_labels()
,
tidy_add_variable_labels()
,
tidy_attach_model()
,
tidy_disambiguate_terms()
,
tidy_identify_variables()
,
tidy_plus_plus()
,
tidy_remove_intercept()
,
tidy_select_variables()
df <- Titanic %>% dplyr::as_tibble() %>% dplyr::mutate(Survived = factor(Survived, c("No", "Yes"))) res <- df %>% glm( Survived ~ Class + Age + Sex, data = ., weights = .$n, family = binomial, contrasts = list(Age = contr.sum, Class = "contr.SAS") ) %>% tidy_and_attach() res %>% tidy_add_reference_rows() res %>% tidy_add_reference_rows(no_reference_row = all_dichotomous()) res %>% tidy_add_reference_rows(no_reference_row = "Class") if (requireNamespace("gtsummary")) { glm( response ~ stage + grade * trt, gtsummary::trial, family = binomial, contrasts = list( stage = contr.treatment(4, base = 3), grade = contr.treatment(3, base = 2), trt = contr.treatment(2, base = 2) ) ) %>% tidy_and_attach() %>% tidy_add_reference_rows() }
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