Recuperación de información métrica a partir de información nométrica con diseños de escalamiento multidimensional incompletos
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Colegio Oficial de Psicólogos del Principado de Asturias
Facultad y Departamento de Psicología de la Universidad de Oviedo
Facultad y Departamento de Psicología de la Universidad de Oviedo
Abstract
La presente investigación tenía por objeto comprobar la eficiencia de tres diseños incompletos para la selección de datos de entrada, en problemas de Escalamiento MultiDimensional, con un número elevado de estímulos. Los diseños comparados fueron un diseño cíclico (Spence y Domoney, 1974), dos diseños aleatorios y un diseño con las desemejanzas más grandes. Cuando se satisfacía el umbral de información propuesto por Spence y Domoney (1974), todos los diseños empleados mostraron un grado de eficiencia similar. Sin embargo, con cantidades de información inferiores, el diseño cíclico fue el que produjo los peores resultados; mientras que los otros dos tipos de diseños mantenían su eficiencia aún por debajo del umbral, siendo los diseños aleatorios los que permitieron obtener soluciones satisfactorias incluso con las cantidades más bajas de información de entrada
The objective of this investigation was to prove the efficiency of three incomplete designs which can be used to select the data entry in MultiDimensional Scaling when the number of stimuli is high. Three types of designs were compared: a ciclic design (Spence & Domoney, 1974), two aleatory designs and a design with the biggest dissimilarities. When the minimum percentage of necessary information proposed by Spence and Domoney was used, all of the designs showed a similar degree of efficiency. However, with lower levels of information the ciclic design showed the worst results, while the other two types of designs mantained their efficiency, being the aleatory designs the ones which allowed to obtain satisfactory solutions even with the lowest percentages of entry information
The objective of this investigation was to prove the efficiency of three incomplete designs which can be used to select the data entry in MultiDimensional Scaling when the number of stimuli is high. Three types of designs were compared: a ciclic design (Spence & Domoney, 1974), two aleatory designs and a design with the biggest dissimilarities. When the minimum percentage of necessary information proposed by Spence and Domoney was used, all of the designs showed a similar degree of efficiency. However, with lower levels of information the ciclic design showed the worst results, while the other two types of designs mantained their efficiency, being the aleatory designs the ones which allowed to obtain satisfactory solutions even with the lowest percentages of entry information
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Fernández, C. A., & Fernández, E. M. A. (2000). Recuperación de información métrica a partir de información nométrica con diseños de escalamiento multidimensional incompletos. Psicothema, 12(2), 308-313
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