di_80_index {DisImpact} | R Documentation |
Calculate disproportionate impact per the 80% index method.
di_80_index(
success,
group,
cohort,
weight,
data,
di_80_index_cutoff = 0.8,
reference_group = "hpg",
check_valid_reference = TRUE
)
success |
A vector of success indicators ( |
group |
A vector of group names of the same length as |
cohort |
(Optional) A vector of cohort names of the same length as |
weight |
(Optional) A vector of case weights of the same length as |
data |
(Optional) A data frame containing the variables of interest. If |
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 |
check_valid_reference |
Check whether |
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.
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).
California Community Colleges Chancellor's Office (2014). Guidelines for Measuring Disproportionate Impact in Equity Plans.
library(dplyr)
data(student_equity)
di_80_index(success=Transfer, group=Ethnicity, data=student_equity) %>%
as.data.frame