Aggregating Conclusive and Inconclusive Information: Data and a Model Based on the Assessment of Threat

This study examined the process of combining conclusive and inconclusive information using a Naval threat assessment simulation. On each of 36 trials, participants interrogated 10 pieces of information (e.g., speed, direction, bearing, etc.) about "targets'' in a simulated radar space. The number of hostile, peaceful, and inconclusive cues was factorially varied across targets. Three models were developed to understand how inconclusive information is used in the judgment of threat. According to one model, inconclusive information is ignored and the judgment of threat is based only on the conclusive information. According to a second model, the amount of dominant conclusive information is normalized by all of the available information. Finally, according to a third model, inconclusive information is partitioned under the assumption that it equally represents both dominant and non-dominant evidence. In Experiment 1, the data of novices (i.e., civilians) were best described by a model that assumes a partitioning of inconclusive evidence. This result was replicated in a second experiment involving variation of the global threat context. In a third experiment involving experts (i.e., Canadian Navy officers), the data of half of the participants were best described by the partitioning model and the data of the other half were best described by the normalizing model. In Experiments 1 and 2, the presence of inconclusive information produced a "dilution effect'', whereby hostile (peaceful) targets were judged as less hostile (peaceful) than the predictions of the Partitioning model. The dilution effect was not evident in the judgments of the Navy officers. (C) 2009 Crown in the right of Canada.