fairml (version 0.8)

health.retirement: Health and Retirement Survey

Description

The University of Michigan Health and Retirement Study (HRS) longitudinal dataset.

Usage

data(health.retirement)

Format

The data contains 38653 observations and 27 variables.

References

https://hrs.isr.umich.edu/about

Examples

data(health.retirement)

# complete data analysis.
health.retirement = health.retirement[complete.cases(health.retirement), ]
# short-hand variable names.
r = health.retirement[, "score"]
s = health.retirement[, c("marriage", "gender", "race", "age")]
p = health.retirement[, setdiff(names(health.retirement), c(names(r), names(s)))]
# drop the second race variable.
p = p[, colnames(p) != "race.ethnicity"]

if (FALSE) {
# the lambda = 0.1 is very helpful in making model estimation succeed.
m = fgrrm(response = r, sensitive = s, predictors = p, ,
      family = "poisson", unfairness = 0.05, lambda = 0.1)
summary(m)
}