Abstract
A methodology is presented for randomly creating “teams” from a data pool of individual response records. Using this approach, the effects of two variables on team monitoring performance were investigated: (1) team size and (2) the decision rule employed in defining the requirements of a “team” response. Size of the simulated teams was varied from two to five members. The decision rule was varied from “parallel” in which a response by any one or more members produced a “team” response to “series” in which a “team” response occurred only if all members responded. “Parallel” teams were found to maximize correct detections while “series” teams eliminated all false alarms. For each decision rule, detection rate increased as a function of team size. For each team size, detection rate deteriorated as the decision rule required more members to respond correctly.
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