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Revista Colombiana de Estadística

Print version ISSN 0120-1751

Rev.Colomb.Estad. vol.29 no.2 Bogotá July/Dec. 2006

 

Imputación de datos en diseños switchback usando un modelo mixto con errores correlacionados

Data Imputation in Switchback Designs Using a Mixed Model with Correlated Errors

LUIS FERNANDO GRAJALES1, LUIS ALBERTO LÓPEZ 2

1Universidad Nacional de Colombia, Departamento de Estadística, Bogotá, Profesor Asistente. E-mail: lfgrajalesh@unal.edu.co
2Universidad Nacional de Colombia, Departamento de Estadística, Bogotá, Profesor Asociado. E-mail: lalopezp@unal.edu.co


Resumen

Se trata el problema de imputar mediciones individuales en datos provenientes de diseños switchback con errores correlacionados, teniendo en cuenta la propuesta de Barroso et al. (1998), donde se considera el BLUP (Best Li- near Unbiased Predictor) para la imputación de datos. Se hizo uso de los valores propios de las matrices de cuadrados medios de los errores de las predicciones para comparar las estructuras de covarianza σ2I, AR(1) y CS asociadas a los errores. Los resultados sugieren que las dos primeras estructuras son más adecuadas que la tercera.

Palabras clave: datos faltantes, mínimos cuadrados generalizados, BLUP, estructura de covarianza.


Abstract

The problem of predicting individual measurements in switchback designs with correlated errors is considered. The predictions and imputations are done using the BLUP (Best Linear Unbiased Predictions), which have been suggested by Barroso et al. (1998). Three covariance structures were compared by the eigenvalues of the matrices of mean square errors. The results suggest that structures σ2I and AR(1) are better than CS.

Key words: Missing data, Generalized least squares, Best linear unbiased prediction, Covariance structure.


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