Published
2006-01-01
ESTIMACIÓN DE INFORMACIÓN FALTANTE, IMPUTACIÓN Y ESTADÍSTICOS DE PRUEBA EN MODELOS MIXTOS A DOS VÍAS DE CLASIFICACIÓN
ESTIMATION OF MISSING DATA, IMPUTATION AND TEST STATISTICS IN TWO-WAY CLASSIFICATION MIXED MODELS
Keywords:
Modelo de medias de celda, modelo mixto, información faltante, estimación e imputación, distribución de formas cuadráticas (es)Cell means model, Mixed model, Missing information, Estimation and imputation, Distribution of quadratic forms (en)
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Se propone una metodología para la estimación de información faltante en modelos mixtos de medias de celda que permite la disminución de la correlación entre la información observada y la información estimada, basada en el método propuesto por Melo & Melo (2005). éste se fundamenta en los métodos de estimación vía máxima verosimilitud, expuesto en Searle (1971), y de covariable, propuesto por Bartlett (1937). Después de realizar la imputación de la información, se plantea una manera de llevar a cabo el análisis de varianza en modelos sin interacción, mediante pruebas ponderadas para los efectos fijos y aleatorios involucrados en el modelo.
We propose a methodology to estimate missing information in mixed cell means models. This methodology improves on that Melo & Melo (2005), which is based on the methods of maximum likelihood estimation and covariate proposed by Bartlett (1937), and reduces the correlation between the observed and estimated information. Once the imputation of the missing information is done, we suggest a way to perform the analysis of variance in models without interaction, by generating a weighted test for the fixed and random effects involved in the model.
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How to Cite
Franco, D. C., & Melo, O. O. (2006). ESTIMATION OF MISSING DATA, IMPUTATION AND TEST STATISTICS IN TWO-WAY CLASSIFICATION MIXED MODELS. Revista Colombiana De Estadística, 29(1), 35-56. https://revistas.unal.edu.co/index.php/estad/article/view/29043
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