single_glmre2: Mixed-Effects Logistic Regression Analysis for a Specified...

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Mixed-Effects Logistic Regression Analysis for a Specified Location

Description

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

Usage

single_glmre2(
  data,
  formula,
  location_var,
  random_effect_var,
  location_index,
  family = NULL
)

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.
family	The family to be used for GLM (e.g., 'binomial' for logistic regression).

Value

The results for sigle 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)))

# Create a binary outcome variable for years of education
dummy_data$education_binary <- ifelse(dummy_data$years_education > 11, 1, 0)

# Define a logistic regression formula
formula <- education_binary ~ 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 logistic regression for a specific location (e.g., district 1)
result_single_glmre <- single_glmre2(dummy_data, formula, location_var, random_effect_var,
 location_index = 1, family = binomial())

# View the result
print(result_single_glmre)

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