Publication: Diseños de observación longitudinales: cambio intra-individual y diferencias inter-individuales observados durante la infancia
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Date
2015-05
Authors
Escolano-Pérez, Elena ; Blanco-Villaseñor, Ángel
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Publisher
Murcia: Universidad de Murcia, Editum
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DOI
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info:eu-repo/semantics/article
Description
Abstract
El estudio del cambio en estudios de medidas repetidas o estudios longitudinales (cross-sectional y/o cross sequential) constituye un área de notable interés en el ámbito de la Psicología del Desarrollo. Las medidas (cualitativas/cuantitativas) que tomamos de participantes, bien intraindividualmente bien interindividualmente, permiten capturar cambios del desarrollo cognitivo. Mediante un estudio empírico de desarrollo cognitivo infantil, comprobaremos si los diseños longitudinales (cross-sectional/cross-sequential) pueden utilizarse o no indistintamente con técnicas de análisis de datos uni- o multivariables. Metodológicamente es posible tratar datos longitudinales en alguna de las soluciones aportadas, uni o multivariable. Sin embargo, y aún cumpliendo los requisitos estadísticos necesarios, los resultados y la interpretación de los mismos pueden ser diferentes. Entendemos que hay soluciones en los programas estadísticos actuales que permiten la utilización de técnicas que aseguren si realmente hay diferencias significativas o no en los datos, independientemente de si son tratados con estructuras uni- o multivariables. Los resultados de bebés estudiados en tres momentos temporales (18, 21 y 24 meses) mediante medidas repetidas muestran que la interpretación afecta de igual
manera a datos de la variabilidad intra/interindividual.
The study of change in repeated measures studies or longitudinal studies (cross-sectional and/or cross sequential) is of considerable interest in the field of developmental psychology. Qualitative and quantitative measures of interindividual and intraindividual variability can be used to capture changes in cognitive development. In the present study, through an empirical analysis of infant cognitive development, we investigate whether or not longitudinal (crosssectional/cross-sequential) research designs can be used interchangeably with univariate or multivariate data analysis techniques. Methodologically, longitudinal data can be processed by univariate or multivariate analysis. However, the results and their interpretation may be different, even when the necessary statistical requirements are performed. Current statistical programs incorporate techniques to test for the presence of significant differences in data, regardless of whether these are evaluated by univariate or multivariate analysis. The results of this study, conducted in infants studied at three time points (18, 21 and 24 months), show that both intraindividual and interindividual variability can be detected by repeated measures analyses.
The study of change in repeated measures studies or longitudinal studies (cross-sectional and/or cross sequential) is of considerable interest in the field of developmental psychology. Qualitative and quantitative measures of interindividual and intraindividual variability can be used to capture changes in cognitive development. In the present study, through an empirical analysis of infant cognitive development, we investigate whether or not longitudinal (crosssectional/cross-sequential) research designs can be used interchangeably with univariate or multivariate data analysis techniques. Methodologically, longitudinal data can be processed by univariate or multivariate analysis. However, the results and their interpretation may be different, even when the necessary statistical requirements are performed. Current statistical programs incorporate techniques to test for the presence of significant differences in data, regardless of whether these are evaluated by univariate or multivariate analysis. The results of this study, conducted in infants studied at three time points (18, 21 and 24 months), show that both intraindividual and interindividual variability can be detected by repeated measures analyses.
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