Andraszewicz, Sandra. Quntitative [i.e. Quantitative] analysis of risky decision making in economic environments. 2014, PhD Thesis, University of Basel, Faculty of Psychology.
Official URL: http://edoc.unibas.ch/diss/DissB_10822
The first manuscript proposes standardized covariance, a measure that can quantitatively describe the strength of the association and similarity between choice options' outcomes. The standardized covariance can also describe how risky one option is with respect to another. It can influence predictions of choice models. The second manuscript shows experimentally how association measured with the standardized covariance can influence people's choices. The third manuscript proposes applying the expected shortfall of an option's outcomes as a measure of risk in the standard risk-value models. In an experiment, the risk-value shortfall model successfully predicted people's preference for options with higher expected value, lower variance and more positively skewed distributions of outcomes, and outperformed competing models.
The fourth manuscript proposes a new version of a reinforcement learning model, which can be applied in a social context. The proposed model can account for the behavior of other people competing for a common pool resource. As experimentally tested, the model could successfully predict human behavior and correlated with the brain activity measured with an fMRI method.
The last manuscript outlines advantages of using Bayes factors instead of p-values for interpretation of results from hierarchical regression analysis. As the results in the manuscript show, the Bayesian approach and the standard null-hypothesis statistical testing can lead to different conclusions.
|Committee Members:||Wagenmakers, Eric-Jan|
|Faculties and Departments:||07 Faculty of Psychology > Departement Psychologie > Abteilung Economic Psychology > Economic Psychology (Rieskamp)|
|Bibsysno:||Link to catalogue|
|Number of Pages:||1 Bd.|
|Last Modified:||30 Jun 2016 10:55|
|Deposited On:||01 Jul 2014 13:12|
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