A pedagogical subset of the National Health and Nutrition Examination Survey (NHANES) dataset, serving as a real-world example for Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). Contains selected records demonstrating intersectional demographic health inequalities.
Format
A data frame with 3,000 rows and 7 variables:
- BMI
Body Mass Index (kg/m^2), a continuous outcome variable.
- Obese
Factor indicating obesity status (No/Yes).
- Age
Age in years at screening, a continuous covariate.
- Gender
Gender of the participant (male/female).
- Race
Self-reported race/ethnicity.
- Education
Educational attainment level.
- Poverty
Poverty to income ratio, a continuous covariate. Some values may be missing.
Source
Derived from the NHANES R package. Original data collected by the
Centers for Disease Control and Prevention (CDC).
Note
This is a teaching/illustration dataset only. It is a non-random subsample and
does not carry the NHANES survey weights or complex sampling design,
so results are not survey-representative and should not be used for
substantive population inference. (For your own survey data, the package
supports design-weighted MAIHDA via the sampling_weights argument of
fit_maihda / maihda.)
Examples
data(maihda_health_data)
# Example usage:
# strata_result <- make_strata(maihda_health_data, vars = c("Gender", "Race", "Education"))
# model <- fit_maihda(BMI ~ Age + (1 | stratum), data = strata_result$data)