Selecting measures is a necessary component of human factors research. Proper selection must take into account the representation problem (how is the assignment of numbers to objects or phenomena justified?) and the uniqueness problem (to what degree is this assignment unique?). Other key human factors measurement issues include subject representativeness, variable representativeness, and setting representativeness. It is difficult to create a single measure that captures essential characteristics of complex systems. Several examples illustrate how theory can guide measurement selection in such diverse human factors research as vigilance, turning off warning alarms, information requirements for military command centers, subjective workload, heart-rate signal analysis, and heat stress in nuclear power plants.
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