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Select helper functions

Source: R/select_helpers.R
select_helpers.Rd

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"))

Usage

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")
)

Arguments

continuous2

(logical)
Whether to include continuous2 variables, default is TRUE. For compatibility with {gtsummary}), see gtsummary::all_continuous2().

dichotomous

(logical)
Whether to include dichotomous variables, default is TRUE.

contrasts_type

(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").

Value

A character vector of column names selected.

See also

scope_tidy()

Examples

# \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>
# }