di_80_index {DisImpact}

Calculate disproportionate impact per the 80% index

Description

Calculate disproportionate impact per the 80% index method.

Usage

di_80_index(
  success,
  group,
  cohort,
  weight,
  data,
  di_80_index_cutoff = 0.8,
  reference_group = "hpg",
  check_valid_reference = TRUE
)

Arguments

success

A vector of success indicators (1/0 or TRUE/FALSE) or an unquoted reference (name) to a column in data if it is specified. It could also be a vector of counts, in which case weight should also be specified (group size).

group

A vector of group names of the same length as success or an unquoted reference (name) to a column in data if it is specified.

cohort

(Optional) A vector of cohort names of the same length as success or an unquoted reference (name) to a column in data if it is specified. disproportionate impact is calculated for every group within each cohort. When cohort is not specified, then the analysis assumes a single cohort.

weight

(Optional) A vector of case weights of the same length as success or an unquoted reference (name) to a column in data if it is specified. If success consists of counts instead of success indicators (1/0), then weight should also be specified to indicate the group size.

data

(Optional) A data frame containing the variables of interest. If data is specified, then success, group, and cohort will be searched within it.

di_80_index_cutoff

A numeric value between 0 and 1 that is used to determine disproportionate impact if the index comparing the success rate of the current group to the reference group falls below this threshold; defaults to 0.80.

reference_group

The reference group value in group that each group should be compared to in order to determine disproportionate impact. By default (='hpg'), the group with the highest success rate is used as reference. The user could also specify a value of 'overall' to use the overall rate as the reference for comparison, or 'all but current' to use the combined success rate of all other groups excluding the current group for each comparison.

check_valid_reference

Check whether reference_group is a valid value; defaults to TRUE. This argument exists to be used in di_iterate as when iterating DI calculations, there may be some scenarios where a specified reference group does not contain any students.

Details

This function determines disproportionate impact based on the 80% index method, as described in this reference from the California Community Colleges Chancellor's Office. It assumes that a higher rate is good ("success"). For rates that are deemed negative (eg, rate of drop-outs, high is bad), then consider looking at the converse of the non-success (eg, non drop-outs, high is good) instead in order to leverage this function properly.

Value

A data frame consisting of:

• cohort (if used),

• group,

• n (sample size),

• success (number of successes for the cohort-group),

• pct (proportion of successes for the cohort-group),

• reference_group (the reference group used to compare and determine disproportionate impact),

• reference (the reference rate used for comparison, corresponding to reference_group),

• di_80_index (ratio of pct to the reference),

• di_indicator (1 if di_80_index < di_80_index_cutoff),

• success_needed_not_di (the number of additional successes needed in order to no longer be considered disproportionately impacted as compared to the reference), and

• success_needed_full_parity (the number of additional successes needed in order to achieve full parity with the reference).

References

California Community Colleges Chancellor's Office (2014). Guidelines for Measuring Disproportionate Impact in Equity Plans.

Examples

library(dplyr)
data(student_equity)
di_80_index(success=Transfer, group=Ethnicity, data=student_equity) %>%
  as.data.frame