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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F24%3A43908906" target="_blank" >RIV/60076658:12510/24:43908906 - isvavai.cz</a>

Výsledek na webu

<a href="https://inproforum.ef.jcu.cz/artkey/inf-990000-0900_Proceedings.php" target="_blank" >https://inproforum.ef.jcu.cz/artkey/inf-990000-0900_Proceedings.php</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.32725/978-80-7694-102-1.02" target="_blank" >10.32725/978-80-7694-102-1.02</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

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

Popis výsledku anglicky

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

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

INPROFORUM 2024. Proceedings of the 18th International Scientific Conference INPROFORUM. Entrepreneurship for Sustainability

ISBN

978-80-7694-102-1

ISSN

—

e-ISSN

2336-6788

Počet stran výsledku

9

Strana od-do

8-16

Název nakladatele

Jihočeská univerzita v Českých Budějovicích, Ekonomická fakulta

Místo vydání

České Budějovice

Místo konání akce

České Budějovice

Datum konání akce

7. 11. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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