Observation oriented modeling revised from a statistical point of view

Observation Oriented Modeling was proposed to overcome some of the problems in the application of statistical inference methods in the behavioral sciences. In this paper, we refine one part of this approach and show how it is connected to methods that are well known in statistical learning. Specifically, we argue that the Moore-Penrose pseudo inverse is superior to the initial solution from a statistical point of view. With this we also show that Observation Oriented Modeling can indeed be appropriate for some tasks in the analysis of observed data. To provide a practical example, we demonstrate the revised method by analyzing the effect of mindfulness training on attentional processes.