iomDisparity.glm: Rank and Replace method of adjustment for racial disparities

In rrevansUM/iomDisparity: Rank and replace method of adjustment for racial disparities

Description

The rank-and-replace method adjusts health status by ranking each sample by a summary index of health status and replacing the health status of each minority individual with that of the correspondingly ranked white, thus preserving the ranking of health status and its rank correlation with SES measures.

Usage

iomDisparity.glm(m, x, y, index, race, family = gaussian, link = "identity",
  ...)

Arguments

formula	model formula in the form "y ~ x", same syntax as base::glm()
data	data frame containing terms from formula, should be of class "data.frame". The first column should be the target "y"
index	vector of locations of health status variables in design matrix X
race	dichotomous race or minority/majority indicator, refer to column in "data"
family	generalized linear model family see help(glm), help(family), defaults to Gamma
link	link function for generalized linear model

Examples

data(iomSample1)
colnames(iomSample1) <- tolower(colnames(iomSample1))
sample.filter <- iomSample1[iomSample1$a_bi_tc_d != 0, ]
vars <- c("a_bi_tc_d","white","urban","bet25_50k","more50k",
          "bet2_5comorb","gt5comorb","age","sex")
sample.red <- sample.filter[, vars]

iomDisparity.glm(formula, data,
                 index = 5:8,
                 race = race,
                 family = Gamma,
                 link = "log")

rrevansUM/iomDisparity documentation built on May 8, 2019, 9:45 a.m.