摘要：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.
其他摘要：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.
