Segregation measures between two groups

TDA's segr: a dissimilarity D-Index, a variance ratio and a Gini coefficient between two groups, across one or more categorical class variables. The D-Index is \(\frac{1}{2}\sum_i |p_{1i} - p_{0i}|\), the share of one group that would have to change class for the two groups' distributions across classes to match exactly.

Usage

tda_segr(
  data,
  group,
  variables = NULL,
  options = list(),
  dir = tempfile("tda")
)

Arguments

data

a data frame.

group

the grouping variable, as a name or a vector: coded 0 and 1 (or FALSE/TRUE).

variables

one or more categorical class variables from data (by name) to compute the measures for, one row of output each. Defaults to every other column in data when group is itself given as a column name (nothing to default to if group was a raw vector instead, since data then has no column of its own to exclude).

options

a named list of further TDA options, passed through.

dir

working directory.

Value

An object carrying a table: one row per variable in variables, with the number of classes, cases in each group, and the three measures.

See also

Other descriptive statistics: tda_brr(), tda_cov(), tda_dstat(), tda_freq(), tda_independence(), tda_ineq(), tda_loglin(), tda_quant(), tda_rcorr(), tda_subm()

Examples

set.seed(1)
n <- 100
d <- data.frame(group = rbinom(n, 1, 0.5),
                class1 = sample(1:3, n, replace = TRUE),
                class2 = sample(1:2, n, replace = TRUE))
tda_segr(d, group = "group", variables = c("class1", "class2"))
#> Call: tda_segr(data = d, group = "group", variables = c("class1", "class2"))
#> 
#> Cases: 
#> 
#>  variable classes cases group0 group1    d_index      v_ratio       gini
#>    class1       3   100     52     48 0.11057692 0.0145697807 0.12980769
#>    class2       2   100     52     48 0.02083333 0.0004335067 0.02083333