Comparison of Imputation Methods for Handling Missing Categorical Data with Univariate Pattern // Una comparación de métodos de imputación de variables categóricas con patrón univariado

Autores/as

  • Juan Armando Torres Munguía Maestría en Estadística Aplicada Instituto Tecnológico y de Estudios Superiores de Monterrey (México)

Palabras clave:

Imputation methods, hot-deck, polytomous regression, random forests, smoking habits, missing categorical data

Resumen

This paper examines the sample proportions estimates in the presence of univariate missing categorical data. A database about smoking habits (2011 National Addiction Survey of Mexico) was used to create simulated yet realistic datasets at rates 5% and 15% of missingness, each for MCAR, MAR and MNAR mechanisms. Then the performance of six methods for addressing missingness is evaluated: listwise, mode imputation, random imputation, hot-deck, imputation by polytomous regression and random forests. Results showed that the most effective methods for dealing with missing categorical data in most of the scenarios assessed in this paper were hot-deck and polytomous regression approaches.

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El presente estudio examina la estimación de proporciones muestrales en la presencia de valores faltantes en una variable categórica. Se utiliza una encuesta de consumo de tabaco (Encuesta Nacional de Adicciones de México 2011) para crear bases de datos simuladas pero reales con 5% y 15% de valores perdidos para cada mecanismo de no respuesta MCAR, MAR y MNAR. Se evalúa el desempeño de seis métodos para tratar la falta de respuesta: listwise, imputación de moda, imputación aleatoria, hot-deck, imputación por regresión politómica y árboles de clasificación. Los resultados de las simulaciones indican que los métodos más efectivos para el tratamiento de la no respuesta en variables categóricas, bajo los escenarios simulados, son hot-deck y la regresión politómica.

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Publicado

2016-11-04

Cómo citar

Torres Munguía, J. A. (2016). Comparison of Imputation Methods for Handling Missing Categorical Data with Univariate Pattern // Una comparación de métodos de imputación de variables categóricas con patrón univariado. Revista De Métodos Cuantitativos Para La Economía Y La Empresa, 17, Páginas 101 a 120. Recuperado a partir de https://www.upo.es/revistas/index.php/RevMetCuant/article/view/2196

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