/mnf-sdg-stunting-overweight-2023

Primary LanguageR

UNICEF-WHO-World Bank Joint Child Malnutrition Estimates

Acknowledgments

Procedure for Generating Stunting and Overweight Modelled Estimates

Contents

  1. Sample Input Data All the JME input files
  • List of high-income-countries (“HIC_list_Nov_2020.csv”)
  • MCI and SDI covariate information from IHME (“GBD 2022 MCI and SDI.csv”)
  • Various economic and health related covariate data used for imputation (“API_NY.GDP.MKTP.CD_DS2_en_csv_v2_4701247.csv” and “WPP2022_Demographic_Indicators_Medium.csv”)
  1. Preparing Covariates
  • R code to perform single imputation of the covariate data (“Imputation of IHME covariate data_single_impute.R”)
  1. Preparing Primary Data
  • R code to calculate (if possible) and impute missing SE information (“1 - SE_clean_and_impute.R”)
  • R code to cross-walk surveys with partial age ranges (“2 - Age_range_analysis.R”).
  • R code to merge covariate and survey data (“3 - Merging of covariate and survey data_single_impute.R”)
  • R code to cross-walk surveys with partial sex coverage, and remove redundant sex combinations (i.e., remove “both” when “male” and “female” are included) (“4 - Sex_cross_walk_single_impute.R”)
  1. Model
  • R functions needed for various modeling stages (“Programs_Feb_2020.R” and “Programs_Cleaning_SE.R”)
  • Programs for analyzing the data (“Overweight_analy.R” and “Stunting_analy.R”)
  • Programs for plotting the estimates (“Plotting_estimates.R”)