Empirical Tests of Intransitivity Predicted by Models of Risky Choice

Recently proposed models of risky choice imply systematic violations of transitivity of preference. Five studies explored whether people show patterns of intransitivity predicted by four descriptive models. To distinguish ?true? violations from those produced by ?error,? a model was fit in which each choice can have a different error rate and each person can have a different pattern of true preferences that need not be transitive. Error rate for a choice is estimated from preference reversals between repeated presentations of the same choice. Results of five studies showed that very few people repeated intransitive patterns. We can retain the hypothesis that transitivity best describes the data of the vast majority of participants. --decision making,errors,gambling effect,reference points,regret,transitivity

Testing Theories of Risky Decision Making Via Critical Tests

Whereas some people regard models of risky decision making as if they were statistical summaries of data collected for some other purpose, I think of models as theories that can be tested by experiments. I argue that comparing theories by means of global indices of fit is not a fruitful way to evaluate theories of risky decision making. I argue instead for experimental science. That is, test critical properties, which are theorems of one model that are violated by a rival model. Recent studies illustrate how conclusions based on fit can be overturned by critical tests. Elsewhere, I have warned against drawin

True-and-error models violate independence and yet they are testable

Birnbaum (2011) criticized tests of transitivity that are based entirely on binary choice proportions. When assumptions of independence and stationarity (iid) of choice responses are violated, choice proportions could lead to wrong conclusions. Birnbaum (2012a) proposed two statistics (correlation and variance of preference reversals) to test iid, using random permutations to simulate p-values. Cha, Choi, Guo, Regenwetter, and Zwilling (2013) defended methods based on marginal proportions but conceded that such methods wrongly diagnose hypothetical examples of Birnbaum (2012a). However, they also claimed that “true and error” models also satisfy independence and also fail in such cases unless they become untestable. This article presents correct true-and-error models; it shows how these models violate iid, how they might correctly identify cases that would be misdiagnosed by marginal proportions, and how they can be tested and rejected. This note also refutes other arguments of Cha et al. (2013), including contentions that other tests failed to violate iid “with flying colors”, that violations of iid “do not replicate”, that type I errors are not appropriately estimated by the permutation method, and that independence assumptions are not critical to interpretation of marginal choice proportions

Utility Measurement: Configural-Weight Theory and the Judge\u27s Point of View

Subjects judged the values of lotteries from 3 points of view: the highest price that a buyer should pay, the lowest price that a seller should accept, and the “fair” price. The rank order of judgments changed as a function of point of view. Data also showed violations of branch independence and monotonicity (dominance). These findings pose difficulties for nonconfigural theories of decision making, such as subjective expected utility theory, but can be described by configural-weight theory. Configural weighting is similar to rank-dependent utility theory, except that the weight of the lowest outcome in a gamble depends on the viewpoint, and 0-valued outcomes receive differential weighting. Configural-weight theory predicted the effect of viewpoint, the violations of branch independence, and the violations of monotonicity, using a single scale of utility that is independent of the lottery and the point of view