Factors that Influence how People Perceive Risk and Choose in a Risky Choice SituationIn everyday life, you face many decisions: Do I go left or right, which hairdresser do I choose, which bike do I buy? In some cases, you know on beforehand the exact results of the various choice options at hand. However, the vast majority of decisions have to be made in uncertainty about the possible outcomes. Still, you probably make many of these uncertain, risky decisions with reasonable confidence. In this master's project, we aim to get a deeper understanding of how you make these risky decisions by studying factors that influence people's choice behavior, such as outcome uncertainty, information cost, and speed stress.
In the first semester, we review the literature to learn what we know about factors that influence risky decision making. In the second semester, the research goals and hypotheses for individual students' projects will be worked out. In the third semester, the goals and hypothesis will be implemented in an empirical study.
Validation of the Diffusion ModelThe diffusion model is a very succesfull model for two-choice response time data. More and more studies apply the diffusion model these days to analyse response time data. Response time data generally contains two variable: response time and accuracy (or choice). The problem of these bivariate data lies in the fact that those two variables are in trade-off: when a participants tries to speed up, her accuracy will generally go down; when a participant wants to become more accurate, she often has to slow down to do so. The most important strength of the diffusion model is that it allows to translate these complicated data into more easily interpretable model parameters. These model parameters are assumed to reflect underlying psychological components of decision making, such as the speed of information processing or the caution with which a participant responds. So, the model allows to learn more about the data than would be possible from the analysis of response time and accuracy separately.
Although the underlying mathematical theory is sound, the validity of the translation to psychological components of decision making naturally has to be backed up by empirical validation studies. In such a validation study, an experimental manipulation of, e.g., response caution ("be cautious!") should result in specific effects on the related model parameter. Although some validation studies have been performed, the vast number of studies that apply the diffusion model today asks for a more regorous and comprehensive test of interpretational validity of the model. A master's project on this subject would have a very good chance to make a serious contribution to the field of response time modeling.