Binary binomial processing trees
Abstract
Multinomial processing tree model played an important role in human information processing. A method is given for learning the form of a processing tree by observing the effects of experimental factors that selectively influence parameters in the tree. A factor selectively influence a parameter if changing the level of the factor changes the value of that parameter, leaving the forma of the tree and other parameter invariant. Although a binary binomial processing tree can have a complex form, an investigator needs only to consider two basic forms, a serial and a parallel tree. Necessary and sufficient conditions for probability influencing two different parameters in an arbitrary processing tree are given. If the conditions are satisfied, a simple form of a serial tree or a simple form of a parallel tree will account for the data.
Degree
Ph.D.
Advisors
Schweickert, Purdue University.
Subject Area
Psychology|Experiments|Cognitive therapy
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