This function uses the information from a model tidy tibble to generate
a data frame exposing the different variables of the model,
data frame that could be used for tidy selection. In addition, columns
"var_type", "var_class" and "contrasts_type" are scoped and their
values are added as attributes to the data frame.
For example, if var_type='continuous' for variable "age", then the
attribute attr(.$age, 'gtsummary.var_type') <- 'continuous' is set.
That attribute is then used in a selector like all_continuous().
Note: attributes are prefixed with "gtsummary." to be compatible with
selectors provided by {gtsummary}.
Arguments
- x
(
data.frame)
A tidy tibble, with a"variable"column, as returned bytidy_identify_variables().- data
(
data.frame)
An optional data frame the attributes will be added to.
Examples
mod <- lm(Sepal.Length ~ Sepal.Width * Species, data = iris)
tt <- mod |> tidy_and_attach() |> tidy_add_contrasts()
scope_tidy(tt) |> str()
#> tibble [1 × 4] (S3: tbl_df/tbl/data.frame)
#> $ (Intercept) : logi NA
#> ..- attr(*, "gtsummary.var_type")= chr "intercept"
#> $ Sepal.Width : num NA
#> ..- attr(*, "gtsummary.var_type")= chr "continuous"
#> ..- attr(*, "gtsummary.var_class")= Named chr "numeric"
#> .. ..- attr(*, "names")= chr "Sepal.Width"
#> $ Species : Factor w/ 0 levels: NA
#> ..- attr(*, "gtsummary.var_type")= chr "categorical"
#> ..- attr(*, "gtsummary.var_class")= Named chr "factor"
#> .. ..- attr(*, "names")= chr "Species"
#> ..- attr(*, "gtsummary.contrasts_type")= chr "treatment"
#> $ Sepal.Width:Species: logi NA
#> ..- attr(*, "gtsummary.var_type")= chr "interaction"
scope_tidy(tt, data = model_get_model_frame(mod)) |> str()
#> 'data.frame': 150 obs. of 3 variables:
#> $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
#> $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#> ..- attr(*, "gtsummary.var_type")= chr "continuous"
#> ..- attr(*, "gtsummary.var_class")= Named chr "numeric"
#> .. ..- attr(*, "names")= chr "Sepal.Width"
#> $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
#> ..- attr(*, "gtsummary.var_type")= chr "categorical"
#> ..- attr(*, "gtsummary.var_class")= Named chr "factor"
#> .. ..- attr(*, "names")= chr "Species"
#> ..- attr(*, "gtsummary.contrasts_type")= chr "treatment"
#> - attr(*, "terms")=Classes 'terms', 'formula' language Sepal.Length ~ Sepal.Width * Species
#> .. ..- attr(*, "variables")= language list(Sepal.Length, Sepal.Width, Species)
#> .. ..- attr(*, "factors")= int [1:3, 1:3] 0 1 0 0 0 1 0 1 1
#> .. .. ..- attr(*, "dimnames")=List of 2
#> .. .. .. ..$ : chr [1:3] "Sepal.Length" "Sepal.Width" "Species"
#> .. .. .. ..$ : chr [1:3] "Sepal.Width" "Species" "Sepal.Width:Species"
#> .. ..- attr(*, "term.labels")= chr [1:3] "Sepal.Width" "Species" "Sepal.Width:Species"
#> .. ..- attr(*, "order")= int [1:3] 1 1 2
#> .. ..- attr(*, "intercept")= int 1
#> .. ..- attr(*, "response")= int 1
#> .. ..- attr(*, ".Environment")=<environment: 0x561105b3b070>
#> .. ..- attr(*, "predvars")= language list(Sepal.Length, Sepal.Width, Species)
#> .. ..- attr(*, "dataClasses")= Named chr [1:3] "numeric" "numeric" "factor"
#> .. .. ..- attr(*, "names")= chr [1:3] "Sepal.Length" "Sepal.Width" "Species"
scope_tidy(tt) |> dplyr::select(dplyr::starts_with("Se")) |> names()
#> [1] "Sepal.Width" "Sepal.Width:Species"
scope_tidy(tt) |> dplyr::select(where(is.factor)) |> names()
#> [1] "Species"
scope_tidy(tt) |> dplyr::select(all_continuous()) |> names()
#> [1] "Sepal.Width"
scope_tidy(tt) |> dplyr::select(all_contrasts()) |> names()
#> [1] "Species"
scope_tidy(tt) |> dplyr::select(all_interaction()) |> names()
#> [1] "Sepal.Width:Species"
scope_tidy(tt) |> dplyr::select(all_intercepts()) |> names()
#> [1] "(Intercept)"