Multiple Imputation in R: A Method to Bridging Data Gaps in Regional Sustainability Analysis

This study builds on research presented last year on the application of advanced statistical methods in R software to analyze sustainability indicators in EU regions.Using R software, a widely used programming language for statistical calculations and data analysis, the study examines the availability of data from the Eurostat database necessary to calculate the Regional Human Development Index (RHDI) at various NUTS levels.The study evaluates missing data for the period 2000-2020 and explores the potential to impute these values using Amelia software in R, a specialized R package for multiple imputations.This method is used to estimate missing values, enhancing analytical quality.Furthermore, the study validates the methodology for setting limits for the Min-Max method used in the calculation of the subindicators of health, education and income.The data processing methodology recommended by the official RHDI guidelines was verified against actual Eurostat data.The objective was to determine whether Eurostat data could be used effectively to calculate indicators to assess the effectiveness of regional sustainability strategies within the EU.