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- Keyword
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- Psychology (23)
- Survivor Interaction Contrast (6)
- Workload capacity (5)
- Efficiency (4)
- General recognition theory (4)
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- Human information processing (4)
- Mental architecture (4)
- Visual word perception (4)
- Capacity coefficient (3)
- Architecture (2)
- Bayesian approaches (2)
- Bayesian models (2)
- Capacity (2)
- Coactive (2)
- Configural information (2)
- Configuration (2)
- Dots (2)
- Emergent features (2)
- Gamma quadrant (2)
- Interactive (2)
- Nonparametric (2)
- Parallel (2)
- Parallel systems (2)
- Processing (2)
- Response time (2)
- Response times (2)
- SIC (2)
- Simple Emergent Feature Processing (2)
- Statistics (2)
- Stochastic dynamics (2)
- Publication Type
Articles 1 - 28 of 28
Full-Text Articles in Physical Sciences and Mathematics
Systems Factorial Technology With R, Joseph W. Houpt, Leslie M. Blaha, John P. Mcintire, Paul R. Havig, James T. Townsend
Systems Factorial Technology With R, Joseph W. Houpt, Leslie M. Blaha, John P. Mcintire, Paul R. Havig, James T. Townsend
Joseph W. Houpt
Systems Factorial Technology (SFT) comprises a set of powerful nonparametric models and measures, together with a theory-driven experiment methodology termed the Double Factorial Paradigm (DFP), for assessing the cognitive information processing mechanisms supporting the processing of multiple sources of information in a given task. We provide an overview of the model-based measures of SFT together with a tutorial on designing a DFP experiment to take advantage of all SFT measures in a single experiment. Illustrative examples are given to highlight the breadth of applicability of these techniques across psychology. We further introduce and demonstrate a new package for performing SFT …
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 …
Configuration As A Source Of Information, Joseph W. Houpt, Robert D. Hawkins, Ami Eidels, James T. Townsend, Michael J. Wenger
Configuration As A Source Of Information, Joseph W. Houpt, Robert D. Hawkins, Ami Eidels, James T. Townsend, Michael J. Wenger
Joseph W. Houpt
No abstract provided.
Configuration As A Source Of Information, Joseph W. Houpt, Robert D. Hawkins, Ami Eidels, James T. Townsend, Michael J. Wenger
Configuration As A Source Of Information, Joseph W. Houpt, Robert D. Hawkins, Ami Eidels, James T. Townsend, Michael J. Wenger
Psychology Faculty Publications
No abstract provided.
Fundamental Properties Of Simple Emergent Feature Processing, Robert D. Hawkins, Joseph W. Houpt, Ami Eidels, James T. Townsend, Michael J. Wenger
Fundamental Properties Of Simple Emergent Feature Processing, Robert D. Hawkins, Joseph W. Houpt, Ami Eidels, James T. Townsend, Michael J. Wenger
Joseph W. Houpt
No abstract provided.
Fundamental Properties Of Simple Emergent Feature Processing, Robert D. Hawkins, Joseph W. Houpt, Ami Eidels, James T. Townsend, Michael J. Wenger
Fundamental Properties Of Simple Emergent Feature Processing, Robert D. Hawkins, Joseph W. Houpt, Ami Eidels, James T. Townsend, Michael J. Wenger
Psychology Faculty Publications
No abstract provided.
From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt
From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt
Joseph W. Houpt
No abstract provided.
A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend
A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend
Joseph W. Houpt
No abstract provided.
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.
A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend
A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend
Psychology Faculty Publications
No abstract provided.
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
Psychology Faculty Publications
No abstract provided.
From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt
From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt
Psychology Faculty Publications
No abstract provided.
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
Psychology Faculty Publications
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 …
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 …
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
Joseph W. Houpt
No abstract provided.
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
Psychology Faculty Publications
No abstract provided.
Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend
Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend
Joseph W. Houpt
Systems Factorial Technology is a powerful framework for investigating the fundamental properties of human information processing such as architecture (i.e., serial or parallel processing) and capacity (how processing efficiency is affected by increased workload). The Survivor Interaction Contrast (SIC) and the Capacity Coefficient are effective measures in determining these underlying properties, based on response-time data. Each of the different architectures, under the assumption of independent processing, predicts a specific form of the SIC along with some range of capacity. In this study, we explored SIC predictions of discrete-state (Markov process) and continuous-state (Linear Dynamic) models that allow for certain types …
Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend
Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend
Psychology Faculty Publications
Systems Factorial Technology is a powerful framework for investigating the fundamental properties of human information processing such as architecture (i.e., serial or parallel processing) and capacity (how processing efficiency is affected by increased workload). The Survivor Interaction Contrast (SIC) and the Capacity Coefficient are effective measures in determining these underlying properties, based on response-time data. Each of the different architectures, under the assumption of independent processing, predicts a specific form of the SIC along with some range of capacity. In this study, we explored SIC predictions of discrete-state (Markov process) and continuous-state (Linear Dynamic) models that allow for certain types …
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.
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
Psychology Faculty Publications
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.
Functional Principal Components Analysis And The Capacity Coefficient, D. Burns, Joseph W. Houpt, M. J. Endres, J. T. Townsend
Functional Principal Components Analysis And The Capacity Coefficient, D. Burns, Joseph W. Houpt, M. J. Endres, J. T. Townsend
Joseph W. Houpt
The capacity coefficient is a well established measure of the efficiency of processing combined sources of information. It has been applied to measure cognitive processes ranging from audio-visual integration to face perception. Recently, the capacity coefficient has also been applied in various clinical situations. Typical clinical analysis, such as structural equation modeling, use scalar values or vectors with limited length as input. We explored the use of functional principal component analysis (fPCA) to allow researchers to describe the capacity coefficient, a continuous function of time, with a small set of discrete values. The fPCA approach was compared with two simple …
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
Joseph W. Houpt
As a fundamental part of our daily lives, visual word processing has received much attention in the psychological literature. Despite the well established perceptual advantages of word and pseudoword context using accuracy, a comparable effect using response times has been elusive. Some researchers continue to question whether the advantage due to word context is perceptual. We use the capacity coefficient, a well established, response time based measure of efficiency to provide evidence of word processing as a particularly efficient perceptual process to complement those results from the accuracy domain.
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend
Psychology Faculty Publications
As a fundamental part of our daily lives, visual word processing has received much attention in the psychological literature. Despite the well established perceptual advantages of word and pseudoword context using accuracy, a comparable effect using response times has been elusive. Some researchers continue to question whether the advantage due to word context is perceptual. We use the capacity coefficient, a well established, response time based measure of efficiency to provide evidence of word processing as a particularly efficient perceptual process to complement those results from the accuracy domain.