di_80_index {DisImpact}  R Documentation 
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 ( 
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 
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 dropouts, high is bad), then consider looking at the converse of the nonsuccess (eg, non dropouts, 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 cohortgroup), 
pct
(proportion of successes for the cohortgroup), 
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 ifdi_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