As a methodological approach to ide

As a methodological approach to identify and decompose variance of a given task into independent components and to isolate the processes of interest, Schweizer (2006a, 2006b, 2008, 2009) introduced the so-called fixed-links modeling approach. Fixed-links modeling is a special kind of confirmatory factor analysis (CFA) for data derived from an experimental repeated-measures design. In many WMC tasks, the task demands are systematically increased from easy conditions, with only a small number of items to be stored and processed in working memory, up to highly demanding conditions, with a large number of items. To depict this experimental manipulation of working memory demands, a latent variable can be derived by means of fixed-links modeling with factor loadings fixed in a way that reflects the increasing order of the conditions. Thus, a condition with higher working memory demands gets a higher weight on the latent variable compared to a condition with lower working memory demands. Because the factor loadings are fixed, it is also possible to derive additional latent variables from the same set of manifest variables (i.e., performance measures in the task conditions) as long as the course of the numbers serving as factor loadings differs from each other. If we assume, for example, that variables such as sensory acuity, a person’s general state of alertness, and/or motivation also influence WMC task performance, then the influence of these variables probably varies within, but not among, task conditions in a systematic way. Consequently, a latent variable can be derived from performance measures in the different task conditions with factor loadings fixed to the same value. In case that factor loadings are fixed, the variance of the latent variable is freely estimated and it is necessary that there is a statistically significant amount of variance to indicate that the latent variable reflects a psychologically meaningful process. Thus, while in traditional CFA the variance of the latent variable is fixed to 1 and the factor loadings are freely estimated, in fixed-links models, the factor loadings are fixed and the variance of the latent variable is freely estimated. Furthermore, while in a traditional CFA all common variance of the manifest variables is assigned to one latent variable , more than only one latent variable1 can be derived from