HCHSsim

Set of R code for the simulation study using HCHS survey sampling design

Overview

This set of R code replicates the results from the simulation study implementing the bootstrap and multiple imputation correction of standard errors from the health outcome model with biomarker calibrated nutrients. The code presented here generates a target population using a three-stage design, draws samples from it using a stratified complex survey sampling scheme, and implements the aforementioned methods for standard error correction.

Required software

The entire pipeline is written in R. All necessary packages are loaded in the headers of the code.

How-to

To run the simulation pipeline, you should:

1. Run generateTargetPopulation.R. This will generate a list of individuals using a three-stage design with stratification, block groups, and households.
2. Run generateTargetPopulationData.R to populate the target population data sets with several variables to be used in this simulation study.
3. Run sampleTargetPopulation.R, which will generate 1000 samples from the target population using a stratified three-stage sampling scheme. Sampling probability weights and design variables are included in the final data sets.
4. Run runBootstrap.R and runMI.R to run the proposed approaches for standard error correction.
5. Run summarize.R to summarize the results from the simulation study. See output files in the ./Output/ folder.