Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Cognition and Perception
Bayesian Approaches To Assessing Architecture And Stopping Rule, Joseph W. Houpt, A. Heathcote, A. Eidels, J. T. Townsend
Bayesian Approaches To Assessing Architecture And Stopping Rule, Joseph W. Houpt, A. Heathcote, A. Eidels, J. T. Townsend
Joseph W. Houpt
Much of scientific psychology and cognitive science can be viewed as a search to understand the mechanisms and dynamics of perception, thought and action. Two processing attributes of particular interest to psychologists are the architecture, or temporal relationships between sub-processes of the system, and the stopping rule, which dictates how many of the sub-processes must be completed for the system to finish. The Survivor Interaction Contrast (SIC) is a powerful tool for assessing the architecture and stopping rule of a mental process model. Thus far, statistical analysis of the SIC has been limited to null-hypothesis- significance tests. In this talk …
An Extension Of Sic Predictions To The Wiener Coactive Model, Joseph W. Houpt, James T. Townsend
An Extension Of Sic Predictions To The Wiener Coactive Model, Joseph W. Houpt, James T. Townsend
Joseph W. Houpt
The survivor interaction contrasts (SIC) is a powerful measure for distinguishing among candidate models of human information processing. One class of models to which SIC analysis can apply are the coactive, or channel summation, models of human information processing. In general, parametric forms of coactive models assume that responses are made based on the first passage time across a fixed threshold of a sum of stochastic processes. Previous work has shown that the SIC for a coactive model based on the sum of Poisson processes has a distinctive down--up--down form, with an early negative region that is smaller than the …
The Statistical Properties Of The Survivor Interaction Contrast, Joseph W. Houpt, James T. Townsend
The Statistical Properties Of The Survivor Interaction Contrast, Joseph W. Houpt, James T. Townsend
Joseph W. Houpt
The Survivor Interaction Contrast (SIC) is a powerful tool for assessing the architecture and stopping rule of a model of mental processes. Despite its demonstrated utility, the methodology has lacked a method for statistical testing until now. In this paper we briefly describe the SIC then develop some basic statistical properties of the measure. These developments lead to a statistical test for rejecting certain classes of models based on the SIC. We verify these tests using simulated data, then demonstrate their use on data from a simple cognitive task.