Biomedical subjects

Craig R Fox

Publications and source records attributed to Craig R Fox.

7 recordsLinked to original sources

PubMed2006

Between ignorance and truth: Partition dependence and learning in judgment under uncertainty.

In 3 studies, participants viewed sequences of multiattribute objects (e.g., colored shapes) appearing with varying frequencies and judged the likelihood of the attributes of those objects. Judged probabilities reflected a compromise between (a) the frequency with which each attribute appeared and (b) the ignorance prior probability cued by the number of distinct values that the focal attribute could take on. Thus, judged probabilities were partition dependent, varying with the number of events into which the state space was subjectively divided. This bias was diminished among participants more confident in what they learned, was strong and insensitive to level of confidence when ignorance priors were especially salient, and required ignorance priors to be salient only when probabilities were elicited (not during encoding).

Attention↗

PubMed2005

Prospect theory on the brain? Toward a cognitive neuroscience of decision under risk.

Most decisions must be made without advance knowledge of their consequences. Economists and psychologists have devoted much attention to modeling decisions made under conditions of risk in which options can be characterized by a known probability distribution over possible outcomes. The descriptive shortcomings of classical economic models motivated the development of prospect theory (D. Kahneman, A. Tversky, Prospect theory: An analysis of decision under risk. Econometrica, 4 (1979) 263-291; A. Tversky, D. Kahneman, Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5 (4) (1992) 297-323) the most successful behavioral model of decision under risk. In the prospect theory, subjective value is modeled by a value function that is concave for gains, convex for losses, and steeper for losses than for gains; the impact of probabilities are characterized by a weighting function that overweights low probabilities and underweights moderate to high probabilities. We outline the possible neural bases of the components of prospect theory, surveying evidence from human imaging, lesion, and neuropharmacology studies as well as animal neurophysiology studies. These results provide preliminary suggestions concerning the neural bases of prospect theory that include a broad set of brain regions and neuromodulatory systems. These data suggest that focused studies of decision making in the context of quantitative models may provide substantial leverage towards a fuller understanding of the cognitive neuroscience of decision making.

Animals↗

PubMed2005

How subjective grouping of options influences choice and allocation: diversification bias and the phenomenon of partition dependence.

The authors argue that people's tendency to diversify their allocations of money and consumption choices over alternatives gives rise to decisions that vary systematically with the subjective grouping of available options. These subjective groupings are influenced by subtle variations in the presentation of options or elicitation of preferences. Studies 1-4 demonstrate such "partition dependence" in allocations of money to beneficiaries, consumption experiences to future time periods, and choices to a menu of consumption options. Study 5 documents weaker partition dependence among individuals with greater relevant experience discriminating among options, and Study 6 shows that the effect is attenuated among participants with stronger or more accessible intrinsic preferences.

Choice Behavior↗

PubMed2004

Partition-edit-count: naive extensional reasoning in judgment of conditional probability.

The authors provide evidence that people typically evaluate conditional probabilities by subjectively partitioning the sample space into n interchangeable events, editing out events that can be eliminated on the basis of conditioning information, counting remaining events, then reporting probabilities as a ratio of the number of focal to total events. Participants' responses to conditional probability problems were influenced by irrelevant information (Study 1), small variations in problem wording (Study 2), and grouping of events (Study 3), as predicted by the partition-edit-count model. Informal protocol analysis also supports the authors' interpretation. A 4th study extends this account from situations where events are treated as interchangeable (chance and ignorance) to situations where participants have information they can use to distinguish among events (uncertainty).

Humans↗

PubMed2004

Typical versus atypical unpacking and superadditive probability judgment.

Probability judgments for packed descriptions of events (e.g., the probability that a businessman does business with a European country) are compared with judgments for unpacked descriptions of the same events (e.g., the probability that a businessman does business with England, France, or some other European country). The prediction that unpacking can decrease probability judgments, derived from the hypothesis that category descriptions are interpreted narrowly in terms of typical instances, is contrasted to the prediction of support theory that unpacking will generally increase judged probabilities (A. Tversky & D. J. Koehler, 1994). The authors varied the typicality of unpacked instances and found no effect of unpacking with typical instances (additivity) and a negative effect with atypical instances (superadditivity). Support theory cannot account for these findings in its current formulation.

Humans↗

PubMed2003

Partition priming in judgment under uncertainty.

We show that likelihood judgments are biased toward an ignorance-prior probability that assigns equal credence to each mutually exclusive event considered by the judge. The value of the ignorance prior depends crucially on how the set of possibilities (i.e., the state space) is subjectively partitioned by the judge. For instance, asking "what is the probability that Sunday will be hotter than any other day next week?" facilitates a two-fold case partition, [Sunday hotter, Sunday not hotter], thus priming an ignorance prior of 1/2. In contrast, asking "what is the probability that the hottest day of the week will be Sunday?" facilitates a seven-fold class partition, [Sunday hottest, Monday hottest, etc.], priming an ignorance prior of 1/7. In four studies, we observed systematic partition dependence: Judgments made by participants presented with either case or class formulations of the same query were biased toward the corresponding ignorance prior.

Bias↗

PubMed2002

Forecasting trial outcomes: lawyers assign higher probability to possibilities that are described in greater detail.

The study of judgment under uncertainty has revealed that people judge the probability of an event to be higher when the event is described as a disjunction of constituent events or when they judge constituent events separately. These observations have motivated the development of support theory (Y. Rottenstreich & A. Tversky, 1997; A. Tversky & D. J. Koehler, 1994), a descriptive model of judgment under uncertainty. The major predictions of support theory are that (1) the judged probabilities of complementary events sum to 1; (2) the judged probabilities of n > 2 exclusive and exhaustive events generally sum to more than 1; and (3) the judged probability of an event generally increases when it is described as a disjunction of specific possibilities. We test these predictions in 6 studies of experienced attorneys who judged the likelihood of particular trial outcomes or were asked to offer advice on whether or not to accept a settlement offer. The results demonstrate that attorneys are indeed susceptible to bias in forecasting trial outcomes, consistent with support theory.

Forecasting↗