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.


Statistical inference Statistical modeling Observation oriented modeling Mindfulness 



Karsten Luebke developed the mathematical framework of this paper. He also wrote substantial parts of this paper. Without his efforts, this work would not have appeared. Unfortunately, limited time ressources did not allow him to finalize the work on this paper; so he decided that he would not appear as author. I am deeply thankful for his contribution. I thankfully acknowledge Jana Lemke who collected the data. Christian Roever and Jane Zagorski provided helpful comments on an earlier draft of the manuscript. I also thank the editor and the reviewers for their constructive comments.

Supplementary material

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© Psychonomic Society, Inc. 2017

Authors and Affiliations

  1. 1.Iwp InstituteFOM University of Applied SciencesNürnbergGermany

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