This paper explores inconsistencies that occur in utility measurement under risk when expected utility theory is assumed and the contribution that prospect theory and some other generalizations of expected utility can make to the resolution of these inconsistencies. We used five methods to measure utilities under risk and found clear violations of expected utility. Of the theories studied, prospect theory was the most consistent with our data. The main improvement of prospect theory over expected utility was in comparisons between a riskless and a risky prospect (riskless-risk methods). We observed no improvement over expected utility in comparisons between two risky prospects (risk-risk methods). An explanation for the latter observation may be that there was less distortion in probability weighting in the interval [0.10, 0.20] than has commonly been observed.utility measurement, nonexpected utility, prospect theory, health

This paper presents a test of the predictive validity of various classes of QALY models (i.e. linear, power and exponential models). We first estimated TTO utilities for 43 EQ-5D chronic health states and next these states were embedded in nonchronic health profiles. The chronic TTO utilities were then used to predict the responses to TTO questions with nonchronic health profiles. We find that the power QALY model clearly outperforms linear and exponential QALY models. Optimal power coefficient is 0.65. Our results suggest that TTO-based QALY calculations may be biased. This bias can be corrected using a power QALY model.

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