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
Famous quotes containing the words integration and/or models:
“The more specific idea of evolution now reached is—a change from an indefinite, incoherent homogeneity to a definite, coherent heterogeneity, accompanying the dissipation of motion and integration of matter.”
—Herbert Spencer (1820–1903)
“Friends broaden our horizons. They serve as new models with whom we can identify. They allow us to be ourselves—and accept us that way. They enhance our self-esteem because they think we’re okay, because we matter to them. And because they matter to us—for various reasons, at various levels of intensity—they enrich the quality of our emotional life.”
—Judith Viorst (20th century)