| di_ppg_iterate {DisImpact} | R Documentation |
Iteratively calculate disproportionate impact via the percentage point gap (PPG) method for many disaggregation variables.
di_ppg_iterate(
data,
success_vars,
group_vars,
cohort_vars,
reference_groups,
repeat_by_vars = NULL,
weight_var = NULL,
min_moe = 0.03,
use_prop_in_moe = FALSE,
prop_sub_0 = 0.5,
prop_sub_1 = 0.5
)
data |
A data frame for which to iterate DI calculation for a set of variables. |
success_vars |
A character vector of success variable names to iterate across. |
group_vars |
A character vector of group (disaggregation) variable names to iterate across. |
cohort_vars |
A character vector of cohort variable names to iterate across. |
reference_groups |
Either 'overall', 'hpg', or a character vector of the same length as 'group_vars' that indicates the reference group value for each group variable in 'group_vars'. |
repeat_by_vars |
A character vector of variables to repeat DI calculations for across all combination of these variables, including '- All' as a group for each variable. The reference rate used for DI comparison differs for every combination of the variables listed here. |
weight_var |
A character scalar specifying the weight variable if the input data set is summarized (ie, the the success variables specified in 'success_vars' contain count of successes). Weight here corresponds to the denominator when calculating the success rate. Defaults to 'NULL' for an input data set where each row describes each individual. |
min_moe |
The minimum margin of error to be used in the PPG calculation, passed to 'di_ppg'. |
use_prop_in_moe |
Whether the estimated proportions should be used in the margin of error calculation by the PPG, passed to 'di_ppg'. |
prop_sub_0 |
Passed to 'di_ppg'. |
prop_sub_1 |
Passed to 'di_ppg'. |
Iteratively calculate disproportionate impact via the percentage point gap (PPG) method for all combinations of 'success_vars', 'group_vars', and 'cohort_vars', for each combination of subgroups specified by 'repeat_by_vars'.
A data frame with all relevant returned fields from 'di_ppg' plus 'success_variable' (elements of 'success_vars'), 'disaggregation' (elements of 'group_vars'), and 'reference_group' (elements of 'reference_groups').
library(dplyr)
data(student_equity)
# Multiple group variables
di_ppg_iterate(data=student_equity, success_vars=c('Transfer')
, group_vars=c('Ethnicity', 'Gender'), cohort_vars=c('Cohort')
, reference_groups='overall')