Evaluando interdependencia en interacciones diádicas utilizando correlación cruzada / No disponible

dependenciade las experiencias emocionales en interacciones diádicas. Consideramos alos dos miembros de la diada (marido y mujer) como un sistema dinámico acoplado yestudiamos la dependencia entre los afectos de ambos individuos utilizando correlacióncruzada (CROSS). Para identificar la posible dirección en el acoplamiento, calculamosCROSS para series retardadas. Hemos utilizados los siguientes valores de retardo T=-1; T=-2, T=0, T=1, T=2. La significación estadística de los índices de sincronizaciónestimados se estableció utilizando el método de surrogate time series(AU)

In this study we use linear synchronization index to evaluate the dependence ofemotional experiences in dyadic interactions. We consider the two members of a dyad(husband and wife) as a coupled dynamical systems and study the dependence betweenboth individuals’affective processes using cross-correlations (CROSS). To identify apossible direction in the coupling, we calculate CROSS for time-delayed series (-1,-2, 0,1, 2,). In addition, we evaluate the statistical significance of each synchronization indexthrough surrogate time series(AU)

What needs to be explained to account for age-related effects on multiple cognitive variables?

Structural equation methodology was used to investigate age-related influences across a number of cognitive variables in 204 adults ranging from 18 to 91 years of age with a hierarchical structure that contained 4 1st-order factors and 1 2nd-order common factor. Direct age relations were found to the common factor as well as to 1st-order speed and memory factors. Replicability of the findings was explored by investigating the same structure of age relations, using 2 different data sets, and a similar patten was found in each. These results suggest that at least 3 statistically distinct types of age-related influences are operating on a wide variety of cognitive variables and presumably require separate explanatory mechanisms.

Comparative longitudinal structural analyses of the growth and decline of multiple intellectual abilities over the life span.

Latent growth curve techniques and longitudinal data are used to examine predictions from the theory of fluid and crystallized intelligence (Gf-Gc theory; J. L. Horn & R. B. Cattell, 1966, 1967). The data examined are from a sample (N approximately 1,200) measured on the Woodcock-Johnson Psycho-Educational Battery-Revised (WJ-R). The longitudinal structural equation models used are based on latent growth models of age using two-occasion "accelerated" data (e.g., J. J. McArdle & R. Q. Bell, 2000; J. J. McArdle & R. W. Woodcock, 1997). Nonlinear mixed-effects growth models based on a dual exponential rate yield a reasonable fit to all life span cognitive data. These results suggest that most broad cognitive functions fit a generalized curve that rises and falls. Novel multilevel models directly comparing growth curves show that broad fluid reasoning (Gf) and acculturated crystallized knowledge (Gc) have different growth patterns. In all comparisons, any model of cognitive age changes with only a single g factor yields an overly simplistic view of growth and change over age.