Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Psychology (3)
- 2010 (2)
- DSM (2)
- Avoidant (1)
- Axis I (1)
-
- Axis II (1)
- Borderline (1)
- CLPS (1)
- Capacity coefficient (1)
- Collaborative Longitudinal Personality Study (1)
- Confidence intervals (1)
- DSM-IV (1)
- Diagnosis (1)
- Efficiency (1)
- Exploratory factor analysis (1)
- FFM (1)
- FPCA (1)
- Functional principal component analysis (1)
- Human information processing (1)
- Mental architecture (1)
- NEO (1)
- NEO-PI-R (1)
- Nonparametric (1)
- Obsessive-Compulsive (1)
- Personality Disorders (1)
- Principal components analysis (1)
- Psychometrics (1)
- Psychopathology research constructs (1)
- Quantitative Methods (1)
- RDoC (1)
- Publication
Articles 1 - 11 of 11
Full-Text Articles in Psychology
Developing Constructs For Psychopathology Research: Research Domain Criteria, Charles A. Sanislow, Daniel S. Pine, Kevin J. Quinn, Michael J. Kozak, Marjorie A. Garvey, Robert K. Heinssen, Philip Sung-En Wang, Bruce N. Cuthbert
Developing Constructs For Psychopathology Research: Research Domain Criteria, Charles A. Sanislow, Daniel S. Pine, Kevin J. Quinn, Michael J. Kozak, Marjorie A. Garvey, Robert K. Heinssen, Philip Sung-En Wang, Bruce N. Cuthbert
Charles A. Sanislow, Ph.D.
There exists a divide between findings from integrative neuroscience and clinical research focused on mechanisms of psychopathology. Specifically, a clear correspondence does not emerge between clusters of complex clinical symptoms and dysregulated neurobiological systems, with many apparent redundancies. For instance, many mental disorders involve multiple disruptions in putative mechanistic factors (e.g., excessive fear, deficient impulse control), and different disrupted mechanisms appear to play major roles in many disorders. The Research Domain Criteria (RDoC) framework is a heuristic to facilitate the incorporation of behavioral neuroscience in the study of psychopathology. Such integration might be achieved by shifting the central research focus …
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 Covariance Sign Of Transformed Random Variables With Applications To Economics And Finance, Martin Egozcue
The Covariance Sign Of Transformed Random Variables With Applications To Economics And Finance, Martin Egozcue
Martin Egozcue
No abstract provided.
Psychometric Characteristics And Clinical Correlates Of Neo-Pi-R Fearless Dominance And Impulsive Antisociality In The Collaborative Longitudinal Personality Disorders Study, Edward A. Witt, Christopher J. Hopwood, Leslie C. Morey, John C. Markowitz, Thomas H. Mcglashan, Carlos M. Grilo, Charles A. Sanislow, M. Tracie Shea, Andrew E. Skodol, John G. Gunderson, M. Brent Donnellan
Psychometric Characteristics And Clinical Correlates Of Neo-Pi-R Fearless Dominance And Impulsive Antisociality In The Collaborative Longitudinal Personality Disorders Study, Edward A. Witt, Christopher J. Hopwood, Leslie C. Morey, John C. Markowitz, Thomas H. Mcglashan, Carlos M. Grilo, Charles A. Sanislow, M. Tracie Shea, Andrew E. Skodol, John G. Gunderson, M. Brent Donnellan
Charles A. Sanislow, Ph.D.
This study evaluates the validity of derived measures of the psychopathic personality traits of Fearless Dominance and Impulsive Antisociality from the NEO Personality Inventory-Revised (NEO-PI-R; Costa & McCrae, 1992) using data from the Collaborative Longitudinal Personality Disorders Study (baseline N = 733). These 3 issues were examined: (a) the stability of the measures over a 10-year interval, (b) their criterion-related validity, and (c) their incremental validity relative to an alternative NEO-PI-R profile-rating approach for assessing psychopathy. NEO-PI-R Fearless Dominance and Impulsive Antisociality scales were relatively stable across 10 years and demonstrated differential associations with measures of personality pathology and psychopathology …
Prospect Theory, Indifference Curves, And Hedging Risks, Udo Broll, Martin Egozcue, Wing Keung Wong, Ricardas Zitikis
Prospect Theory, Indifference Curves, And Hedging Risks, Udo Broll, Martin Egozcue, Wing Keung Wong, Ricardas Zitikis
Martin Egozcue
The prospect theory is one of the most popular decision-making theories. It is based on S-shaped utility functions, unlike the von Neumann and Morgenstern (NM) theory, which is based on concave utility functions. The S-shaped functions bring challenges, and extensions and generalizations of the NM theory into the prospect theory are not always possible. For example, in the prospect theory, the monotonicity of indifference curves depends on the underlying mean, unlike in the NM theory. Risk-hedging deci- sions also become more complex within the prospect theory. In this paper, we discuss these topics and establish general results concerning certain covariances …
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 …
Estimating Confidence Intervals For Eigenvalues In Exploratory Factor Analysis, Ross Larsen, Russell Warne
Estimating Confidence Intervals For Eigenvalues In Exploratory Factor Analysis, Ross Larsen, Russell Warne
Russell T Warne
Exploratory factor analysis (EFA) has become a common procedure in educational and psychological research. In the course of performing an EFA, researchers often base the decision of how many factors to retain on the eigenvalues for the factors. However, many researchers do not realize that eigenvalues, like all sample statistics, are subject to sampling error, which means that confidence intervals (CIs) can be estimated for each eigenvalue. In the present article, we demonstrate two methods of estimating CIs for eigenvalues: one based on the mathematical properties of the central limit theorem, and the other based on bootstrapping. References to appropriate …
Segregation And Integration: A Study Of The Behaviors Of Investors With Extended Value Functions, Martin Egozcue, Wing Keung Wong
Segregation And Integration: A Study Of The Behaviors Of Investors With Extended Value Functions, Martin Egozcue, Wing Keung Wong
Martin Egozcue
This paper extends prospect theory, mental accounting, and the hedonic editing model by developing an analytical theory to explain the behavior of investors with extended value functions in segregating or integrating multiple outcomes when evaluating mental accounting.
Gruss Type Bounds For The Covariance Of Transformed Random Variables, Martin Egozcue, Luis Fuentes García, Wing Keung Wong, Ricardas Zitikis
Gruss Type Bounds For The Covariance Of Transformed Random Variables, Martin Egozcue, Luis Fuentes García, Wing Keung Wong, Ricardas Zitikis
Martin Egozcue
No abstract provided.
Gains From Diversification On Convex Combinations: A Majorization And Stochastic Dominance Approach, Martin Egozcue, Wing Keung Wong
Gains From Diversification On Convex Combinations: A Majorization And Stochastic Dominance Approach, Martin Egozcue, Wing Keung Wong
Martin Egozcue
By incorporating both majorization theory and stochastic dominance theory, this paper presents a gen- eral theory and a unifying framework for determining the diversification preferences of risk-averse inves- tors and conditions under which they would unanimously judge a particular asset to be superior. In particular, we develop a theory for comparing the preferences of different convex combinations of assets that characterize a portfolio to give higher expected utility by second-order stochastic dominance. Our findings also provide an additional methodology for determining the second-order stochastic dominance efficient set.
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.