Integration Models
There are three main types of algebraic models used in information integration theory: adding, averaging, and multiplying.
Adding models
R = reaction/overt behavior
F/G = contributing factors
R1 = F1 + G1 (Condition 1)
R2 = F2 + G2 (Condition 2)
Typically an experiment is designed so that:
R1 = R2, and
F1 > F2, so that
G1 < G2
There are two special cases known as discounting and augmentation.
Discounting: The value of any factor is reduced if other factors that produce the same effect are added.
Example: F2 is not present or has a value of zero. If F1 is positive, then G1 must be less than G2.
Augmentation: An inverse version of the typical model.
Example: If F1 is negative, then G1 must be greater than G2
Two advantages of adding models; (1) Participants are not required to have an exact intuitive calculation, (2) The adding model itself need not be completely valid. Certain kinds of interaction among the factors would not affect the qualitative conclusions.
Read more about this topic: Information Integration Theory
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