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Additive factors and stages of mental processes in task networks
Authors:Richard Schweickert  Donald L. Fisher
Affiliation:
  • a Department of Psychological Sciences, Purdue University, West Lafayette, IN 47907, United States
  • b Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA 01003, United States
  • c Department of Psychology, University of Chicago, United States
  • Abstract:To perform a task a subject executes mental processes. An experimental manipulation, such as a change in stimulus intensity, is said to selectively influence a process if it changes the duration of that process leaving other process durations unchanged. For random process durations a definition of a factor selectively influencing a process by increments is given in terms of stochastic dominance (also called “the usual stochastic order”). A technique for analyzing reaction times, Sternberg’s Additive Factor Method, assumes all the processes are in series. When all processes are in series, each process is called a stage. With the Additive Factor Method, if two experimental factors selectively influence two different stages by increments, the factors will have additive effects on reaction time. An assumption of the Additive Factor Method is that if two experimental factors interact, then they influence the same stage. We consider sets of processes in which some pairs of processes are sequential and some are concurrent (i.e., the processes are partially ordered). We propose a natural definition of a stage for such sets of processes. For partially ordered processes, with our definition of a stage, if two experimental factors selectively influence two different processes by increments, each within a different stage, then the factors have additive effects. If each process selectively influenced by increments is in the same stage, then an interaction is possible, although not inevitable.
    Keywords:Selective influence   Reaction time   Additive factor method   Critical path network   Directed acyclic graph   Serial   Parallel processing   Stochastic dominance   Usual stochastic order
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