No-Respuesta De Items En Estudios De Mercado
AbstractStatistical procedures for missing data have improved significantly in the last years. This study put the missing data in context and makes a revision of the recent literature for the case that the missing data problem is ignorable. In an application, based in real data of a psychographic profile study, several different methods to treat missing data are implemented. The results of this exercise show that most of the traditional imputation procedures induce bias and do not consider the whole variability in the estimates. Multiple imputation, based on Bayesian models and data augmentation gives the best results in the application.
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Bibliographic InfoArticle provided by Escuela de Administracion. Pontificia Universidad Católica de Chile. in its journal ABANTE.
Volume (Year): 5 (2002)
Issue (Month): 1 ()
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
- James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
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