Markus Steiner
University of Basel
6 Papers
Markus Steiner is an academic researcher from University of Basel. The author has contributed to research in topics: Test validity & Convergent validity. The author has an hindex of 5, co-authored 6 publications.
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Papers
EFAtools: An R package with fast and flexible implementations of exploratory factor analysis tools
Markus Steiner,Silvia Grieder +1 more
TL;DR: Exploratory factor analysis (EFA) is a data-driven approach to factor analysis and is used to extract a smaller number of common factors that represent or explain the common variance of a larger set of manifest variables.
Neuroimaging in moderate MDMA use: A systematic review.
F. Mueller,Claudia Lenz,Markus Steiner,Patrick C. Dolder,Marc Walter,Undine E. Lang,Matthias E. Liechti,Stefan Borgwardt +7 more
TL;DR: There is no convincing evidence that moderate MDMA use is associated with structural or functional brain alterations in neuroimaging measures, and the lack of significant results was associated with high methodological heterogeneity in terms of dosages and co-consumption of other drugs, low quality of studies and small sample sizes.
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Representative design in psychological assessment: A case study using the Balloon Analogue Risk Task (BART).
Markus Steiner,Renato Frey +1 more
TL;DR: In this paper, the Balloon Analogue Risk Task (BART) was investigated and it was found that the typical implementation of this task violates the principle of representative design, thus conflicting with the expectations people likely form from real balloons, which may explain the previously observed limitations in some of the BART's psychometric properties.
Through the Window of My Mind: Mapping Information Integration and the Cognitive Representations Underlying Self-Reported Risk Preference
Markus Steiner,Florian Ismael Seitz,Renato Frey +2 more
- 01 Apr 2021
TL;DR: In this paper, the authors investigate the information-integration processes underlying people's self-reports by means of cognitive modeling and examine people's cognitive representations of their risk preferences, finding that interindividual differences in self-reported risk preferences can be modeled well based on the listed aspects' properties of evidence and substantially better than using sociodemographic variables as predictors.
Modeling Choice Paradoxes Under Risk: From Prospect Theories to Sampling-Based Accounts
TL;DR: Overall, the results suggest that researchers should move away from CPT, and focus their efforts on alternative models such as DFTe, as it is able to accommodate the choice data at large in a parsimonious fashion.
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