Multinomiale Modelle in der kognitiven Psychologie

Gegenstand der vorliegenden Arbeit ist eine Klasse von stochastischen Modellen, die sich vor allem in den letzten zehn Jahren in ganz unterschiedlichen Anwendungskontexten immer wieder als sehr nützlich erwiesen hat. Dies gilt prinzipiell für das Gesamtgebiet der empirischen Psychologie, vor allem aber für die kognitive Psychologie. Multinomiale Modelle sind nach meiner Auffassung besser als andere Ansätze geeignet, eine Verbindung zwischen psychologischen Theorien und psychologischen Daten herzustellen, die einerseits den Kriterien der formalen Präzision und der empirischen Prüfbarkeit genügt, andererseits aber auch einfach, flexibel und robust genug ist, um auf viele unterschiedliche Problemstellungen anwendbar zu sein, auch solche, bei denen auf vorhandene Ansätze formaler Theoriebildung bislang noch nicht zurückgegriffen werden kann. Wie zu zeigen sein wird, erscheint es auf dem Hintergrund vorliegender Befunde zur multinomialen Modellierung immerhin denkbar, daß das „Joch der precision-importance trade-off function” (Schwarz, 1991) in der Psychologie prinzipiell überwindbar ist. Wissenschaftliche Genauigkeit und Eindeutigkeit muß nicht immer mit einem Verlust an praktischer Bedeutsamkeit erkauft werden und umgekehrt muß die Optimierung des Anwendungsaspekts und die Erweiterung des Anwendungsspektrums nicht zwangsläufig einen Verzicht auf Präzision nach sich ziehen

Nudged to Win: Designing Robo-Advisory to Overcome Decision Inertia

Decision inertia is a serious problem in financial decision-making and thus a challenge for decision support systems. We discuss recent findings and review antecedents and consequences of decision inertia from a psychological perspective. We use these insights to develop IT-based methods designed to overcome decision inertia using psychologically optimized financial decision support systems. Furthermore, we propose an experimental study to evaluate the design features of such a system. Our work is a first step in designing adaptive decision support systems that detect situations in which the user is prone to decision inertia and react by adapting interface elements appropriately that might otherwise exacerbate decision inertia – for a specific user in a specific decision situation

Alcohol-induced retrograde facilitation? Mixed evidence in a preregistered replication and encoding-maintenance-retrieval analysis

Somewhat counterintuitively, alcohol consumption following learning of new information has been shown to enhance performance on a delayed subsequent memory test. This phenomenon has become known as the retrograde facilitation effect (Parker et al., 1981). Although conceptually replicated repeatedly, serious methodological problems are associated with most previous demonstrations of retrograde facilitation. Moreover, two potential explanations have been proposed, the interference and the consolidation hypothesis. So far, empirical evidence for and against both hypotheses is inconclusive (Wixted, 2004). To scrutinize the existence of the effect, we conducted a pre-registered replication that avoided common methodological pitfalls. In addition, we used Küpper-Tetzel and Erdfelder’s (2012) multinomial processing tree (MPT) model to disentangle encoding, maintenance, and retrieval contributions to memory performance. With a total sample size of N = 93, we found no evidence for retrograde facilitation in overall cued or free recall of previously presented word pairs. In line with this, MPT analyses also showed no reliable difference in maintenance probabilities. However, MPT analyses revealed a robust alcohol advantage in retrieval. We conclude that alcohol-induced retrograde facilitation might exist and be driven by an underlying retrieval benefit. Future research is needed to investigate potential moderators and mediators of the effect explicitly

Testing interactions in multinomial processing tree models

Multinomial processing tree (MPT) models allow testing hypotheses on latent psychological processes that underlie human behavior. However, past applications of this model class have mainly been restricted to the analysis of main effects. In this paper, we adopt the interaction concept as defined in log-linear models and show why it is appropriate for MPT models. We then explain how to implement and test ordinal and disordinal two-way interaction hypotheses in MPT models. We also show how our method generalizes to higher-order interactions involving three or more factors. An empirical example from source memory and aging demonstrates the applicability of this method and allows for directly testing the associative deficit theory that age differences are larger in associative (e.g., source) memory as opposed to item memory. Throughout the paper, we explain how most analytic steps can be easily implemented in the freely available software multiTree