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

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  • Torres Munguía, Juan Armando

    (Instituto Tecnológico y de Estudios Superiores de Monterrey (México))

Abstract

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. || 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.

Suggested Citation

  • Torres Munguía, Juan Armando, 2014. "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 = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 17(1), pages 101-120, June.
    • Handle: RePEc:pab:rmcpee:v:17:y:2014:i:1:p:101-120
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    References listed on IDEAS

    as
    1. Cristina Barceló, 2008. "The impact of alternative imputation methods on the measurement of income and wealth: Evidence from the Spanish survey of household finances," Working Papers 0829, Banco de España.
    2. Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
    3. G. Chauvet & J.-C. Deville & D. Haziza, 2011. "On balanced random imputation in surveys," Biometrika, Biometrika Trust, vol. 98(2), pages 459-471.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    imputation methods; hot-deck; polytomous regression; random forests; smoking habits; missing categorical data; métodos de imputación; hot-deck; regresión politómica; árboles de clasificación; hábitos de consumo de tabaco; valores perdidos en variables categóricas;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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