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The dimensional effects of missing information on choice processing
Author(s) -
Burke Sandra J.
Publication year - 1995
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.3960080402
Subject(s) - missing data , dimension (graph theory) , information processing , computer science , inference , data mining , artificial intelligence , cognitive psychology , mathematics , machine learning , psychology , pure mathematics
This paper demonstrates that choice processing may be different in missing information situations than in full information situations depending on whether inferences are used to fill in missing values and the overlap of the missing information itself. It is shown that when individuals do not form inferences to fill in missing values, fewer full attribute‐based processes and more processes which accommodate for missing attribute values, alternative‐based or given‐dimension attribute‐based, are used. It is also shown that when a processing shift due to missing information does occur, the overlap of the missing values will affect the type of shift that takes place. If overlap is high, a shift to given‐dimension attribute‐based processing is more likely, and when overlap is low, a shift to alternative‐based processing is more likely. When individuals do form inferences to fill in missing values, processing is more similar to that in full information situations. Finally, it is shown that individuals will often partially fill in missing information, thus moderating the proposed effects.