set.seed(123)
library(dplyr)
# Create dummy data
dummy_data <- data.frame(
years_education = rnorm(100, 12, 3), # Represents years of education
gender_female = rbinom(100, 1, 0.5), # 1 = Female, 0 = Male
household_wealth = sample(1:5, 100, replace = TRUE), # Wealth index from 1 to 5
district_code = sample(1:10, 100, replace = TRUE) # Represents district codes
) %>% arrange(district_code)
# Create HHid (Household ID), grouping every 3-4 records, and convert to character
dummy_data$HHid <- as.character(rep(1:20, each = 5, length.out = nrow(dummy_data)))
# Define a simple regression formula
formula <- years_education ~ gender_female + household_wealth:gender_female
location_var <- "district_code"
random_effect_var <- "HHid"
# Run mixed-effects regression for all districts
results <- DHSr::Replmre2(dummy_data, formula, location_var, random_effect_var)
print(head(results))
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