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Order model terms by dictionary variables and category levels

Source: R/index.R
index_terms.Rd

A convenience wrapper for broom::tidy() output that attaches variable and category metadata from the dictionary, then sorts rows into dictionary order via index_rows().

Usage

index_terms(
  data,
  dictionary = NULL,
  term_separator = "",
  term_colname = "term",
  names = "name",
  levels = "level"
)

Arguments

data

A data frame of model output, typically from broom::tidy(). Must contain a column identifying model terms (see term_colname).

dictionary

A data dictionary object. If NULL, uses the default dictionary set via set_default_dictionary().

term_separator

A string used to separate variable names and category values when constructing or matching terms. Default is "" to match the default separator that most R modeling functions use.

term_colname

Name of the column in data that contains term identifiers. Default is "term".

names

Character value giving the column name that stores the variable name in the enriched output. Default is "name".

levels

Character value giving the column name that stores the category code/level in the enriched output. Default is "level".

Value

The same type as data (with term-key columns appended), rows sorted to match the variable and category order defined in the dictionary.

Examples


library(broom)

dd <- as_data_dictionary(iris) |>
  set_variable_order(Species, .before = 1)

fit <- tidy(lm(Sepal.Length ~ ., data = iris))

index_terms(fit, dictionary = dd)
#> # A tibble: 7 × 9
#>   name        level label reference term  estimate std.error statistic   p.value
#>   <chr>       <chr> <chr> <lgl>     <chr>    <dbl>     <dbl>     <dbl>     <dbl>
#> 1 (Intercept) NA    NA    FALSE     (Int…    2.17     0.280       7.76  1.43e-12
#> 2 Species     seto… seto… TRUE      Spec…   NA       NA          NA    NA       
#> 3 Species     vers… vers… FALSE     Spec…   -0.724    0.240      -3.01  3.06e- 3
#> 4 Species     virg… virg… FALSE     Spec…   -1.02     0.334      -3.07  2.58e- 3
#> 5 Sepal.Width NA    NA    FALSE     Sepa…    0.496    0.0861      5.76  4.87e- 8
#> 6 Petal.Leng… NA    NA    FALSE     Peta…    0.829    0.0685     12.1   1.07e-23
#> 7 Petal.Width NA    NA    FALSE     Peta…   -0.315    0.151      -2.08  3.89e- 2