Abstract
Cognitive psychologists often make use of regression coefficient analyses to analyse repeated measures data, as proposed by Lorch and Myers (1990). In this paper, it is demonstrated that in case this procedure is applicable and the data are balanced, using hierarchical linear models gives the same results after one single analysis. In addition, the hierarchical linear model approach is more flexible and has a broader applicability, for example including nonbalanced designs. Despite the relative complexity of the approach, we therefore recommend cognitive researchers considering the use of these models to analyse repeated measures data.
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