Description Usage Arguments Examples
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.
1 2 | iomDisparity.glm(m, x, y, index, race, family = gaussian, link = "identity",
...)
|
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 |
1 2 3 4 5 6 7 8 9 10 11 12 | 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")
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