Missing Categorical Data in Sociological Surveys: An Experimental Evaluation of Imputation Techniques

Missing Categorical Data in Sociological Surveys: An Experimental Evaluation of Imputation Techniques

Missing categorical data presents a persistent challenge to data quality in quantitative sociological research, where simpler approaches can lead to biased estimates and incorrect conclusions. This article provides an empirically grounded evaluation of multiple imputation (MI) strategies for categor...

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Bibliographic Details
Main Authors: Yaroslav Kostenko, Andrii Gorbachyk
Format: Article
Language:English
Published: Taras Shevchenko National University of Kyiv 2025-06-01
Series:Соціологічні студії
Subjects:
data quality
missing data
data imputation
multiple imputation
logistic regression
clustering
Online Access:https://sociostudios.vnu.edu.ua/index.php/socio/article/view/417
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