Set of functions to supplement the tidyselect set of functions for selecting columns of data frames (and other items as well).
all_continuous()
selects continuous variables
all_categorical()
selects categorical (including "dichotomous"
) variables
all_dichotomous()
selects only type "dichotomous"
all_interaction()
selects interaction terms from a regression model
all_intercepts()
selects intercept terms from a regression model
all_contrasts()
selects variables in regression model based on their type
of contrast
all_ran_pars()
and all_ran_vals()
for random-effect parameters and
values from a mixed model
(see vignette("broom_mixed_intro", package = "broom.mixed")
)
all_continuous(continuous2 = TRUE)
all_categorical(dichotomous = TRUE)
all_dichotomous()
all_interaction()
all_ran_pars()
all_ran_vals()
all_intercepts()
all_contrasts(
contrasts_type = c("treatment", "sum", "poly", "helmert", "sdif", "other")
)
(logical
)
Whether to include continuous2 variables, default is TRUE
.
For compatibility with {gtsummary}
), see gtsummary::all_continuous2()
.
(logical
)
Whether to include dichotomous variables, default is TRUE
.
(string
)
Type of contrast to select. When NULL
, all variables with a
contrast will be selected. Default is NULL
. Select among contrast types
c("treatment", "sum", "poly", "helmert", "sdif", "other")
.
A character vector of column names selected.
# \donttest{
glm(response ~ age * trt + grade, gtsummary::trial, family = binomial) |>
tidy_plus_plus(exponentiate = TRUE, include = all_categorical())
#> # A tibble: 5 × 18
#> term variable var_label var_class var_type var_nlevels contrasts
#> <chr> <chr> <chr> <chr> <chr> <int> <chr>
#> 1 trtDrug A trt Chemotherapy Trea… character dichoto… 2 contr.tr…
#> 2 trtDrug B trt Chemotherapy Trea… character dichoto… 2 contr.tr…
#> 3 gradeI grade Grade factor categor… 3 contr.tr…
#> 4 gradeII grade Grade factor categor… 3 contr.tr…
#> 5 gradeIII grade Grade factor categor… 3 contr.tr…
#> # ℹ 11 more variables: contrasts_type <chr>, reference_row <lgl>, label <chr>,
#> # n_obs <dbl>, n_event <dbl>, estimate <dbl>, std.error <dbl>,
#> # statistic <dbl>, p.value <dbl>, conf.low <dbl>, conf.high <dbl>
# }
# \donttest{
glm(response ~ age + trt + grade + stage,
gtsummary::trial,
family = binomial,
contrasts = list(trt = contr.SAS, grade = contr.sum, stage = contr.poly)
) |>
tidy_plus_plus(
exponentiate = TRUE,
include = all_contrasts(c("treatment", "sum"))
)
#> # A tibble: 5 × 18
#> term variable var_label var_class var_type var_nlevels contrasts
#> <chr> <chr> <chr> <chr> <chr> <int> <chr>
#> 1 trtDrug A trt Chemotherapy Trea… character dichoto… 2 contr.SAS
#> 2 trtDrug B trt Chemotherapy Trea… character dichoto… 2 contr.SAS
#> 3 grade1 grade Grade factor categor… 3 contr.sum
#> 4 grade2 grade Grade factor categor… 3 contr.sum
#> 5 grade3 grade Grade factor categor… 3 contr.sum
#> # ℹ 11 more variables: contrasts_type <chr>, reference_row <lgl>, label <chr>,
#> # n_obs <dbl>, n_event <dbl>, estimate <dbl>, std.error <dbl>,
#> # statistic <dbl>, p.value <dbl>, conf.low <dbl>, conf.high <dbl>
# }