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Author: Jeffrey N. Rouder
Publisher: Wiley-Blackwell
ISBN: 9781405132084
Category : Psychology
Languages : en
Pages : 344
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Book Description
There has always been a strong mathematical and statistical component in experimental psychology. Many current articles in high-ranking journals present sophisticated, nonlinear statistical and mathematical models for solving substantive problems. This high level of discourse represents advances in both methodological practice and scientific knowledge. It also presents a challenge to the research community: how do we teach the skills necessary to understand mathematical and statistical approaches? There are several excellent texts on psychological statistics. These focus on the general linear model and cover topics such as ANOVA and regression. They do not provide coverage of simple nonlinear models that have been instrumental in modern cognition and perception. There are a few texts in mathematical psychology,but these do not focus on statistical issues of parameter estimation, inference,and model selection. In brief, there is an unfilled niche in graduate education for a text that covers practical aspects of using formal models in cognition and perception. The theme of the book is that modeling can be done in a united statistical framework. The framework is based on two features: (1) models can be placed in a nested structure with general models nesting more specific ones; and (2) estimation and inference for all of these models can be done with maximum likelihood techniques. Using a pragmatic approach, this book will show students how to solve problems with statistical models. Further, the approach stresses the relationship between psychological theory and statistical models. Many theories of psychological process are neither linear nor additive; analysis of data to test these theories can be more profitably done outside of the general linear model framework. One of the tenets of this book is that theoretical or experimental concerns motivate appropriate statistical models. This task of motivating statistical models with psychological concerns is greatly aided by a nested-models framework.
Author: Jeffrey N. Rouder
Publisher: Wiley-Blackwell
ISBN: 9781405132084
Category : Psychology
Languages : en
Pages : 344
Get Book Here
Book Description
There has always been a strong mathematical and statistical component in experimental psychology. Many current articles in high-ranking journals present sophisticated, nonlinear statistical and mathematical models for solving substantive problems. This high level of discourse represents advances in both methodological practice and scientific knowledge. It also presents a challenge to the research community: how do we teach the skills necessary to understand mathematical and statistical approaches? There are several excellent texts on psychological statistics. These focus on the general linear model and cover topics such as ANOVA and regression. They do not provide coverage of simple nonlinear models that have been instrumental in modern cognition and perception. There are a few texts in mathematical psychology,but these do not focus on statistical issues of parameter estimation, inference,and model selection. In brief, there is an unfilled niche in graduate education for a text that covers practical aspects of using formal models in cognition and perception. The theme of the book is that modeling can be done in a united statistical framework. The framework is based on two features: (1) models can be placed in a nested structure with general models nesting more specific ones; and (2) estimation and inference for all of these models can be done with maximum likelihood techniques. Using a pragmatic approach, this book will show students how to solve problems with statistical models. Further, the approach stresses the relationship between psychological theory and statistical models. Many theories of psychological process are neither linear nor additive; analysis of data to test these theories can be more profitably done outside of the general linear model framework. One of the tenets of this book is that theoretical or experimental concerns motivate appropriate statistical models. This task of motivating statistical models with psychological concerns is greatly aided by a nested-models framework.
Author: Joseph W. Houpt
Publisher: Routledge
ISBN: 1317297482
Category : Psychology
Languages : en
Pages : 288
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Book Description
In this two volume festschrift, contributors explore the theoretical developments (Volume I) and applications (Volume II) in traditional cognitive psychology domains, and model other areas of human performance that benefit from rigorous mathematical approaches. It brings together former classmates, students and colleagues of Dr. James T. Townsend, a pioneering researcher in the field since the early 1960s, to provide a current overview of mathematical modeling in psychology. Townsend’s research critically emphasized a need for rigor in the practice of cognitive modeling, and for providing mathematical definition and structure to ill-defined psychological topics. The research captured demonstrates how the interplay of theory and application, bridged by rigorous mathematics, can move cognitive modeling forward.
Author: Joseph W. Houpt
Publisher: Psychology Press
ISBN: 1317297512
Category : Psychology
Languages : en
Pages : 306
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Book Description
In this two volume festschrift, contributors explore the theoretical developments (Volume I) and applications (Volume II) in traditional cognitive psychology domains, and model other areas of human performance that benefit from rigorous mathematical approaches. It brings together former classmates, students and colleagues of Dr. James T. Townsend, a pioneering researcher in the field since the early 1960s, to provide a current overview of mathematical modeling in psychology. Townsend’s research critically emphasized a need for rigor in the practice of cognitive modeling, and for providing mathematical definition and structure to ill-defined psychological topics. The research captured demonstrates how the interplay of theory and application, bridged by rigorous mathematics, can move cognitive modeling forward.
Author: Jerome R. Busemeyer
Publisher: SAGE
ISBN: 0761924507
Category : Psychology
Languages : en
Pages : 225
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Book Description
Responding to an explosion of new mathematical and computational models used in the fields of cognitive science, this book provides simple tutorials concerning the development and testing of such models. The authors focus on a few key models, with a primary goal of equipping readers with the fundamental principles, methods, and tools necessary for evaluating and testing any type of model encountered in the field of cognitive science.
Author: F. Gregory Ashby
Publisher: Psychology Press
ISBN: 1317784030
Category : Education
Languages : en
Pages : 582
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Book Description
The mental representations of perceptual and cognitive stimuli vary on many dimensions. In addition, because of quantal fluctuations in the stimulus, spontaneous neural activity, and fluctuations in arousal and attentiveness, mental events are characterized by an inherent variability. During the last several years, a number of models and theories have been developed that explicitly assume the appropriate mental representation is both multidimensional and probabilistic. This new approach has the potential to revolutionize the study of perception and cognition in the same way that signal detection theory revolutionized the study of psychophysics. This unique volume is the first to critically survey this important new area of research.
Author: John C. Dunn
Publisher: Springer
ISBN: 3319731297
Category : Psychology
Languages : en
Pages : 126
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Book Description
This book provides an introduction to the theory, method, and practice of State-Trace Analysis (STA), and includes a detailed tutorial on the statistical analysis of state-trace designs. The book offers instructions on how to perform state-trace analysis using the authors' own publicly-available software in both Matlab and R. The book begins by discussing the general framework for thinking about the relationships between independent variables, latent variables, and dependent variables. Subsequent chapters provide a software package that can be used to fit state-trace models as well as additional designs and examples. The book concludes with a discussion on potential extensions of STA and additional aspects of its application. State-Trace Analysis will be of interest to researchers and graduate students working in experimental, applied, and cognitive psychology.
Author: Joseph W. Houpt
Publisher: Psychology Press
ISBN: 9781138600263
Category :
Languages : en
Pages : 284
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Book Description
In this two volume festschrift, contributors explore the theoretical developments (Volume I) and applications (Volume II) in traditional cognitive psychology domains, and model other areas of human performance that benefit from rigorous mathematical approaches. It brings together former classmates, students and colleagues of Dr. James T. Townsend, a pioneering researcher in the field since the early 1960s, to provide a current overview of mathematical modeling in psychology. Townsend¿s research critically emphasized a need for rigor in the practice of cognitive modeling, and for providing mathematical definition and structure to ill-defined psychological topics. The research captured demonstrates how the interplay of theory and application, bridged by rigorous mathematics, can move cognitive modeling forward.
Author: Howard Bowman
Publisher: World Scientific
ISBN: 9814482935
Category : Computers
Languages : en
Pages : 319
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Book Description
This book collects together refereed versions of papers presented at the Eighth Neural Computation and Psychology Workshop (NCPW 8). NCPW is a well-established workshop series that brings together researchers from different disciplines, such as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology. The articles are centred on the theme of connectionist modelling of cognition and perceptionn.The proceedings have been selected for coverage in:• Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings)• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)• Index to Social Sciences & Humanities Proceedings® (ISSHP® / ISI Proceedings)• Index to Social Sciences & Humanities Proceedings (ISSHP CDROM version / ISI Proceedings)• CC Proceedings — Engineering & Physical Sciences• CC Proceedings — Biomedical, Biological & Agricultural Sciences
Author: Song-Chun Zhu
Publisher: Springer Nature
ISBN: 3030965309
Category : Computers
Languages : en
Pages : 365
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Book Description
As the first book of a three-part series, this book is offered as a tribute to pioneers in vision, such as Béla Julesz, David Marr, King-Sun Fu, Ulf Grenander, and David Mumford. The authors hope to provide foundation and, perhaps more importantly, further inspiration for continued research in vision. This book covers David Marr's paradigm and various underlying statistical models for vision. The mathematical framework herein integrates three regimes of models (low-, mid-, and high-entropy regimes) and provides foundation for research in visual coding, recognition, and cognition. Concepts are first explained for understanding and then supported by findings in psychology and neuroscience, after which they are established by statistical models and associated learning and inference algorithms. A reader will gain a unified, cross-disciplinary view of research in vision and will accrue knowledge spanning from psychology to neuroscience to statistics.
Author: Brandon M. Turner
Publisher: Springer
ISBN: 303003688X
Category : Psychology
Languages : en
Pages : 109
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Book Description
This book presents a flexible Bayesian framework for combining neural and cognitive models. Traditionally, studies in cognition and cognitive sciences have been done by either observing behavior (e.g., response times, percentage correct, etc.) or by observing neural activity (e.g., the BOLD response). These two types of observations have traditionally supported two separate lines of study, which are led by two different cognitive modelers. Joining neuroimaging and computational modeling in a single hierarchical framework allows the neural data to influence the parameters of the cognitive model and allows behavioral data to constrain the neural model. This Bayesian approach can be used to reveal interactions between behavioral and neural parameters, and ultimately, between neural activity and cognitive mechanisms. Chapters demonstrate the utility of this Bayesian model with a variety of applications, and feature a tutorial chapter where the methods can be applied to an example problem. The book also discusses other joint modeling approaches and future directions. Joint Models of Neural and Behavioral Data will be of interest to advanced graduate students and postdoctoral candidates in an academic setting as well as researchers in the fields of cognitive psychology and neuroscience.
