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  1. Machine Learning in Psychometrics and Psychological Research.Graziella Orrù, Merylin Monaro, Ciro Conversano, Angelo Gemignani & Giuseppe Sartori - 2020 - Frontiers in Psychology 10:492685.
    Recent controversies about the level of replicability of behavioral research analyzed using statistical inference have cast interest in developing more efficient techniques for analyzing the results of psychological experiments. Here we claim that complementing the analytical workflow of psychological experiments with Machine Learning-based analysis will both maximize accuracy and minimize replicability issues. As compared to statistical inference, ML analysis of experimental data is model agnostic and primarily focused on prediction rather than inference. We also highlight some potential pitfalls resulting from (...)
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  • Why Psychology Needs to Stop Striving for Novelty and How to Move Towards Theory-Driven Research.Juliane Burghardt & Alexander Neil Bodansky - 2021 - Frontiers in Psychology 12:609802.
    Psychological science is maturing and therefore transitioning from explorative to theory-driven research. While explorative research seeks to find something “new,” theory-driven research seeks to elaborate on already known and hence predictable effects. A consequence of these differences is that the quality of explorative and theory-driven research needs to be judged by distinct criterions that optimally support their respective development. Especially, theory-driven research needs to be judged by its methodological rigor. A focus on innovativeness, which is typical for explorative research, will (...)
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