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Feldman, Naomi H.; Griffiths, Thomas L.; Morgan, James L. – Psychological Review, 2009
A variety of studies have demonstrated that organizing stimuli into categories can affect the way the stimuli are perceived. We explore the influence of categories on perception through one such phenomenon, the perceptual magnet effect, in which discriminability between vowels is reduced near prototypical vowel sounds. We present a Bayesian model…
Descriptors: Statistical Inference, Classification, Stimuli, Vowels
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Okada, Kensuke; Shigemasu, Kazuo – Applied Psychological Measurement, 2009
Bayesian multidimensional scaling (MDS) has attracted a great deal of attention because: (1) it provides a better fit than do classical MDS and ALSCAL; (2) it provides estimation errors of the distances; and (3) the Bayesian dimension selection criterion, MDSIC, provides a direct indication of optimal dimensionality. However, Bayesian MDS is not…
Descriptors: Bayesian Statistics, Multidimensional Scaling, Computation, Computer Software
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Ruscio, John – Assessment, 2009
Determining whether individuals belong to different latent classes (taxa) or vary along one or more latent factors (dimensions) has implications for assessment. For example, no instrument can simultaneously maximize the efficiency of categorical and continuous measurement. Methods such as taxometric analysis can test the relative fit of taxonic…
Descriptors: Classification, Measurement, Measurement Techniques, Evaluation Research
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Reali, Florencia; Griffiths, Thomas L. – Cognition, 2009
The regularization of linguistic structures by learners has played a key role in arguments for strong innate constraints on language acquisition, and has important implications for language evolution. However, relating the inductive biases of learners to regularization behavior in laboratory tasks can be challenging without a formal model. In this…
Descriptors: Language Research, Linguistic Input, Bayesian Statistics, Repetition
Zajonc, Tristan – ProQuest LLC, 2012
Effective policymaking requires understanding the causal effects of competing proposals. Relevant causal quantities include proposals' expected effect on different groups of recipients, the impact of policies over time, the potential trade-offs between competing objectives, and, ultimately, the optimal policy. This dissertation studies causal…
Descriptors: Public Policy, Policy Formation, Bayesian Statistics, Economic Development
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Pullenayegum, Eleanor M.; Guo, Qing; Hopkins, Robert B. – Journal of Statistics Education, 2012
Graduate students in the health sciences who hope to become independent researchers must be able to write up their results at a standard suitable for submission to peer-reviewed journals. Bayesian analyses are still rare in the medical literature, and students are often unclear on what should be included in a manuscript. Whilst there are published…
Descriptors: Bayesian Statistics, Critical Thinking, Graduate Students, Health Sciences
Proctor, Thomas P.; Kim, YoungKoung Rachel – College Board, 2010
The purpose of this paper is to provide information about how students' scores change when they retake the PSAT/NMSQT as juniors or take the SAT in the spring after they take the PSAT/NMSQT as juniors. Two research questions guided this study and motivated the approach for analysis of the data: How do scores change for students who took the…
Descriptors: Scores, Achievement Gains, Bayesian Statistics, College Entrance Examinations
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Rouder, Jeffrey N.; Yue, Yu; Speckman, Paul L.; Pratte, Michael S.; Province, Jordan M. – Psychological Review, 2010
A dominant theme in modeling human perceptual judgments is that sensory neural activity is summed or integrated until a critical bound is reached. Such models predict that, in general, the shape of response time distributions change across conditions, although in practice, this shape change may be subtle. An alternative view is that response time…
Descriptors: Reaction Time, Decision Making, Models, Statistical Analysis
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Mariano, Louis T.; McCaffrey, Daniel F.; Lockwood, J. R. – Journal of Educational and Behavioral Statistics, 2010
There is an increasing interest in using longitudinal measures of student achievement to estimate individual teacher effects. Current multivariate models assume each teacher has a single effect on student outcomes that persists undiminished to all future test administrations (complete persistence [CP]) or can diminish with time but remains…
Descriptors: Persistence, Academic Achievement, Data Analysis, Teacher Influence
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Leenen, Iwin; Van Mechelen, Iven; Gelman, Andrew; De Knop, Stijn – Psychometrika, 2008
Hierarchical classes models are models for "N"-way "N"-mode data that represent the association among the "N" modes and simultaneously yield, for each mode, a hierarchical classification of its elements. In this paper we present a stochastic extension of the hierarchical classes model for two-way two-mode binary data. In line with the original…
Descriptors: Simulation, Bayesian Statistics, Models, Classification
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Vouloumanos, Athena – Cognition, 2008
A language learner trying to acquire a new word must often sift through many potential relations between particular words and their possible meanings. In principle, statistical information about the distribution of those mappings could serve as one important source of data, but little is known about whether learners can in fact track multiple…
Descriptors: Language Acquisition, Word Recognition, Cognitive Mapping, Bayesian Statistics
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Norris, Dennis; Kinoshita, Sachiko – Journal of Experimental Psychology: General, 2008
The authors argue that perception is Bayesian inference based on accumulation of noisy evidence and that, in masked priming, the perceptual system is tricked into treating the prime and the target as a single object. Of the 2 algorithms considered for formalizing how the evidence sampled from a prime and target is combined, only 1 was shown to be…
Descriptors: Bayesian Statistics, Inferences, Intuition, Perception
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Park, Joonwook; Desarbo, Wayne S.; Liechty, John – Psychometrika, 2008
Multidimensional scaling (MDS) models for the analysis of dominance data have been developed in the psychometric and classification literature to simultaneously capture subjects' "preference heterogeneity" and the underlying dimentional structure for a set of designated stimuli in a parsimonious manner. There are two major types of latent utility…
Descriptors: Multidimensional Scaling, Models, Bayesian Statistics, Data Analysis
Ayers, Elizabeth; Nugent, Rebecca; Dean, Nema – International Working Group on Educational Data Mining, 2009
A fundamental goal of educational research is identifying students' current stage of skill mastery (complete/partial/none). In recent years a number of cognitive diagnosis models have become a popular means of estimating student skill knowledge. However, these models become difficult to estimate as the number of students, items, and skills grows.…
Descriptors: Data Analysis, Skills, Knowledge Level, Students
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Pardos, Zachary A.; Dailey, Matthew D.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
The well established, gold standard approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pre-test and post-test design. RCTs have been used in the intelligent tutoring community for decades to determine which questions and tutorial feedback work best. Practically speaking, however,…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Pretests Posttests, Educational Research
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