Overprecision is the most robust type of overconfidence. We present a new method that significantly reduces this bias and offers insight into its underlying cause. In three experiments, overprecision was significantly reduced by forcing participants to consider all possible outcomes of an event. Each participant was presented with the entire range of possible outcomes divided into intervals, and estimated each interval’s likelihood of including the true answer. The superiority of this Subjective Probability Interval Estimate (SPIES) method is robust to range widths and interval grain sizes. Its carryover effects are observed even in subsequent estimates made using the conventional, 90 % confidence interval method: judges who first made SPIES judgments considered a broader range of values in subsequent conventional interval estimates as well.

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This report summarizes a variety of the most useful and commonly applied methods for obtaining Dempster-Shafer structures, and their mathematical kin probability boxes, from empirical information or theoretical knowledge. The report includes a review of the aggregation methods for handling agreement and conflict when multiple such objects are obtained from different sources.

1. The choice to not use all available information Debates about statistical foundations can be annoying to practitioners but are important in that foundational claims are used to make general recommendations for practice. All statistical methods allow prior information to be used in the design of a study, or in choosing what variables to include and how to transform them, or in the interpretation of results. What distinguishes Bayesian methods is the expression of prior information in the form of probability distributions on parameters in a model. But this is controversial. Most directly, technical arguments about the efficiency of different statistical procedures translate directly into ethical concerns. As quantitative researchers, we are supposed to use the most accurate estimates and the most honest statements of uncertainty, using statistically inferior methods only in response to other concerns such as simplicity, cost, or substantive theory. For example, in his “bread and peace ” model, political scientist Douglas Hibbs forecasts presidential election outcomes given only two variables, one summarizing economic trends in the year or so leading up to the election and the other being a measure of