The process of vicarious functioning, by which equivalent judgments can result from different patterns of cues, is central to any theory of judgment. It is argued that linear regression and process-tracing models capture the various aspects of vicarious functioning: the former by dealing with the ambiguities that the organism faces with regard to the substitutions and trade-offs between cues in a redundant environment, and the latter by dealing with cue search and attention. Furthermore, although the surface structures and levels of detail of the two models are different, it is shown that process-tracing protocols can be generated via a general additive rule. Therefore, both types of models can be capturing the same underlying process, although at different levels of generality. Two experiments in which both models are built and tested on the same data are presented, and the results are discussed with respect to links between judgment, choice, and task structure; rule generality and awareness; and advantages of a multimethod approach.

Information displays influence decision processes by facilitating some decision strategies while hindering others. Component characteristics of displays, such as the form, organization, and sequence of information, influence decision processes through an adaptive mechanism whereby a decision maker balances the desire to maximize accuracy against the desire to minimize effort. Variations in the information display lead to changes in the anticipated effort and anticipated accuracy of each available strategy and, therefore, provide an incentive for decision makers to use different decision processes. Research in this area can provide guidance regarding the use of displays and other decision-aiding approaches.

Research on cognitive processes in decision making has identified heuristics that often work well but sometimes lead to serious errors. This paper presents an investigation of the performance of heuristics in a complex dynamic setting, characterized by repeated decisions with feedback. There are three components: (1) A simulated task resembling medical decision problems (diagnosis and treatment) is described. (2) Computer models of decision strategies are developed. These include models based on cognitive heuristics as well as benchmark strategies that indicate the limit of the heuristic strategies' performance. The upper benchmark is based on statistical decision theory, the lower one on random trial and error. (3) Selected task characteristics are systematically varied and their influence on performance evaluated in simulation experiments. Results indicate that task characteristics often studied in past research (e.g., symptom diagonosticity, disease base-rates) have less influence on performance relative to feedback-related aspects of the task. These dynamic characteristics are a major determinant of when heuristics perform well or badly. The results also provide insights about the costs and benefits of various cognitive heuristics. In addition, the possible contribution of this research to the design and evaluation of decision aids is considered.decision strategies, heuristics, medical decisions

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