Calculate all inequality indices in one call — calc_all_inequality

Convenience wrapper that computes SII, RII, concentration index, Atkinson index (for multiple \(\varepsilon\) values), and Gini coefficient and returns them as a tidy data frame.

Usage

calc_all_inequality_indices(
  data,
  health_var,
  group_var,
  weight_var,
  epsilon_values = c(0.5, 1, 2)
)

Arguments

data: A data frame with health and group columns.
health_var: Name of the health variable column (character).
group_var: Name of the socioeconomic group column (ordered integer, 1 = most deprived).
weight_var: Name of the population share column (sums to 1).
epsilon_values: Numeric vector of \(\varepsilon\) values for the Atkinson index (default: c(0.5, 1, 2)).

Value

A tibble with columns index, value, and description.

Examples

df <- tibble::tibble(
  group      = 1:5,
  mean_hale  = c(60, 63, 66, 69, 72),
  pop_share  = rep(0.2, 5)
)
calc_all_inequality_indices(df, "mean_hale", "group", "pop_share")
#> Warning: essentially perfect fit: summary may be unreliable
#> # A tibble: 7 × 3
#>   index                   value description                   
#>   <chr>                   <dbl> <chr>                         
#> 1 sii                  15       Slope Index of Inequality     
#> 2 rii                   0.227   Relative Index of Inequality  
#> 3 concentration_index   0.0364  Concentration Index (standard)
#> 4 gini                  0.0364  Gini coefficient              
#> 5 atkinson_epsilon_0.5  0.00104 Atkinson index (epsilon = 0.5)
#> 6 atkinson_epsilon_1    0.00207 Atkinson index (epsilon = 1)  
#> 7 atkinson_epsilon_2    0.00414 Atkinson index (epsilon = 2)