… Methods: A discrete choice experiment was conducted in a nationally representative sample
of 900 Dutch respondents. Simulated maximum likelihood methods were used to estimate …

… in decision making have incorporated both risk and … the different uncertainty representations
and decision models. We … the representation, decision and optimization models to clarify the …

… to the CPT uncertainties. First, we show how to constrain these uncertainties either using …
Second, we show how to integrate these uncertainties in the BBN-based analysis through …

… I introduce a discrete choice model, the Bayesian probit, which … to uncertainty and may
lead to errors in mating choices … available mate options can increase the risk of exposure to …

… for modeling any kind of situation that involves uncertainty, … letting us really see the uncertainty
in our models, as our unknown … of model risk and go over several examples of how model …

… standard discrete choice model, then deriving marginal utility and relative importance for
each attribute in relation to one another. This study will then use the discrete choice model with …

… and must be accounted for in risk-sensitive applications. We … these uncertainties on learned
Q-values. We derive unbiased estimators of these uncertainties and introduce an uncertainty-…

… An efficient design yielded 36 choice sets. Exploded logit choice models were estimated.
Flavour bans are modelled by restricting flavour coefficients in the estimated model. …

… The risk is that they give pictures of consumers that do not … data collection methods, discrete
choice models, and statisti… to testing axioms for choice under uncertainty, and there was no …

… a discrete choice experiment that includes the risk of large production losses due to pests.
Our results indicate that this risk … Risk (or uncertainty 4 ) is an important driver of farmers' …