single_lmre2: Mixed-Effects Regression Analysis for Specified Location

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Mixed-Effects Regression Analysis for Specified Location

Description

This function runs a mixed-effects regression model for a specified location within a dataset.

Usage

single_lmre2(data, formula, location_var, random_effect_var, location_index)

Arguments

data	The dataset to be analyzed.
formula	The formula for the regression model.
location_var	The variable indicating different locations (e.g., 'REGCODE').
random_effect_var	The variable to be used as a random effect (e.g., 'hhid').
location_index	The specific location index or number for which the model should be run.

Value

the results for the specified location to test

Examples

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

# Set the location and random effect variables
location_var <- "district_code"
random_effect_var <- "HHid"

# Run the mixed-effects regression for a specific location (e.g., district 1)
result_single_lmre <- single_lmre2(dummy_data, formula, location_var,
random_effect_var, location_index = 1)

# View the result
print(result_single_lmre)

DHSr documentation built on April 4, 2025, 12:18 a.m.