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Articles 1 - 6 of 6
Full-Text Articles in Social and Behavioral Sciences
Capacity Coefficient Variations, Joseph W. Houpt, Andrew Heathcote, Ami Eidels, Nathan Medeiros-Ward, Jason Watson, David Strayer
Capacity Coefficient Variations, Joseph W. Houpt, Andrew Heathcote, Ami Eidels, Nathan Medeiros-Ward, Jason Watson, David Strayer
Joseph W. Houpt
The capacity coefficient has become an increasingly popular measure of efficiency under changes in workload. It has been used in applications ranging from psychophysical detection tasks to complex cognitive tasks, as well as in addressing questions in social and clinical psychology. The basic formulation compares response times to each stimulus property (or task) in isolation to response times with all stimulus properties (or tasks) at the same time. A number of variations on the basic capacity coefficient have been used, both in the experimental design and in the calculations, and many more are possible. Here we outline the theoretical reasons …
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, Joseph W. Houpt, James T. Townsend, Noah H. Silbert
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, Joseph W. Houpt, James T. Townsend, Noah H. Silbert
Joseph W. Houpt
No abstract provided.
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 …
Bayesian Approaches To Assessing Architecture And Stopping Rule, Joseph W. Houpt, Andrew Heathcote, Ami Eidels, J. T. Townsend
Bayesian Approaches To Assessing Architecture And Stopping Rule, Joseph W. Houpt, Andrew Heathcote, Ami Eidels, J. T. Townsend
Psychology Faculty Publications
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 …
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, James T. Townsend, Joseph W. Houpt, Noah H. Silbert
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, James T. Townsend, Joseph W. Houpt, Noah H. Silbert
Joseph W. Houpt
General Recognition Theory (GRT; Ashby & Townsend, 1986) is a multidimensional theory of classification. Originally developed to study various types of perceptual independence, it has also been widely employed in diverse cognitive venues, such as categorization. The initial theory and applications have been static, that is, lacking a time variable and focusing on patterns of responses, such as confusion matrices. Ashby proposed a parallel, dynamic stochastic version of GRT with application to perceptual independence based on discrete linear systems theory with imposed noise \citep{Ash89}. The current study again focuses on cognitive/perceptual independence within an identification classification paradigm. We extend stochastic …
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, James T. Townsend, Joseph W. Houpt, Noah H. Silbert
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, James T. Townsend, Joseph W. Houpt, Noah H. Silbert
Psychology Faculty Publications
General Recognition Theory (GRT; Ashby & Townsend, 1986) is a multidimensional theory of classification. Originally developed to study various types of perceptual independence, it has also been widely employed in diverse cognitive venues, such as categorization. The initial theory and applications have been static, that is, lacking a time variable and focusing on patterns of responses, such as confusion matrices. Ashby proposed a parallel, dynamic stochastic version of GRT with application to perceptual independence based on discrete linear systems theory with imposed noise (Ashby, 1989). The current study again focuses on cognitive/perceptual independence within an identification classification paradigm. We extend …