Three Boundary Conditions for Computing the Fixed-Point Property in Binary Mixture Data.

Three Boundary Conditions for Computing the Fixed-Point Property in Binary Mixture Data.

Blog Article

The notion of "mixtures" has become pervasive in behavioral and cognitive sciences, due to the success of dual-process theories of cognition.However, providing support for such dual-process theories Youth is not trivial, as it crucially requires properties in the data that are specific to mixture of cognitive processes.In theory, one such property could be the fixed-point property of binary mixture data, applied-for instance- to response times.In that case, the fixed-point property entails that response time distributions obtained in an experiment in which the mixture proportion is manipulated would have a common density point.

In the current article, we discuss the application of the fixed-point property and identify three boundary conditions under which the fixed-point property will not be interpretable.In Boundary condition 1, a finding in support of the fixed-point will be mute because of a lack of difference between conditions.Boundary condition 2 refers to the case in which the extreme conditions are so different that a mixture may display bimodality.In this case, a mixture hypothesis is clearly supported, yet the fixed-point may not be found.

In Boundary Developer and Photoconductor Unit Pack condition 3 the fixed-point may also not be present, yet a mixture might still exist but is occluded due to additional changes in behavior.Finding the fixed-property provides strong support for a dual-process account, yet the boundary conditions that we identify should be considered before making inferences about underlying psychological processes.