di_prop_index {DisImpact}  R Documentation 
Calculate disproportionate impact per the proportionality index (PI) method.
Description
Calculate disproportionate impact per the proportionality index (PI) method.
Usage
di_prop_index(success, group, cohort, weight, data, di_prop_index_cutoff = 0.8)
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_prop_index_cutoff 
A numeric value between 0 and 1 that is used to determine disproportionate impact if the proportionality index falls below this threshold; defaults to 0.80. 
Details
This function determines disproportionate impact based on the proportionality index (PI) 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_success
(proportion of successes attributed to the group within the cohort), 
pct_group
(proportion of sample attributed to the group within the cohort), 
di_prop_index
(ratio of pct_success to pct_group), 
di_indicator
(1 ifdi_prop_index < di_prop_index_cutoff
), and 
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).
When di_prop_index < 1
, then there are signs of disproportionate impact.
References
California Community Colleges Chancellor's Office (2014). Guidelines for Measuring Disproportionate Impact in Equity Plans.
Examples
library(dplyr)
data(student_equity)
di_prop_index(success=Transfer, group=Ethnicity, data=student_equity) %>%
as.data.frame