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Palardy, Gregory J. – Educational and Psychological Measurement, 2010
This article examines the multilevel linear crossed random effects growth model for estimating teacher and school effects from repeated measurements of student achievement. Results suggest that even a small degree of unmodeled nonlinearity can result in a substantial upward bias in the magnitude of the teacher effect, which raises concerns about…
Descriptors: Computation, Models, Statistical Analysis, Academic Achievement
Feeney, Aidan; Wilburn, Catherine – Cognition, 2008
Although Sloutsky agrees with our interpretation of our data, he argues that the totality of the evidence supports his claim that children make inductive generalisations on the basis of similarity. Here we take issue with his characterisation of the alternative hypotheses in his informal analysis of the data, and suggest that a thorough Bayesian…
Descriptors: Bayesian Statistics, Logical Thinking, Child Development, Children
Hohwy, Jakob; Roepstorff, Andreas; Friston, Karl – Cognition, 2008
Binocular rivalry occurs when the eyes are presented with different stimuli and subjective perception alternates between them. Though recent years have seen a number of models of this phenomenon, the mechanisms behind binocular rivalry are still debated and we still lack a principled understanding of why a cognitive system such as the brain should…
Descriptors: Stimuli, Bayesian Statistics, Brain, Probability
Wang, Lijuan; McArdle, John J. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
The main purpose of this research is to evaluate the performance of a Bayesian approach for estimating unknown change points using Monte Carlo simulations. The univariate and bivariate unknown change point mixed models were presented and the basic idea of the Bayesian approach for estimating the models was discussed. The performance of Bayesian…
Descriptors: Simulation, Bayesian Statistics, Comparative Analysis, Computation
Zhang, Zhiyong; McArdle, John J.; Wang, Lijuan; Hamagami, Fumiaki – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Bayesian methods are becoming very popular despite some practical difficulties in implementation. To assist in the practical application of Bayesian methods, we show how to implement Bayesian analysis with WinBUGS as part of a standard set of SAS routines. This implementation procedure is first illustrated by fitting a multiple regression model…
Descriptors: Bayesian Statistics, Computer Software, Monte Carlo Methods, Multiple Regression Analysis
Weaver, Rhiannon – Cognitive Science, 2008
Model validation in computational cognitive psychology often relies on methods drawn from the testing of theories in experimental physics. However, applications of these methods to computational models in typical cognitive experiments can hide multiple, plausible sources of variation arising from human participants and from stochastic cognitive…
Descriptors: Models, Prediction, Cognitive Psychology, Computation
Sharma, Richa – International Journal on E-Learning, 2011
Building intelligent course designing systems adaptable to the learners' needs is one of the key goals of research in e-learning. This goal is all the more crucial as gaining knowledge in an e-learning environment depends solely on computer mediated interaction within the learner group and among the learners and instructors. The patterns generated…
Descriptors: Electronic Learning, Educational Environment, Instructional Design, Student Needs
Iverson, Geoffrey J.; Wagenmakers, Eric-Jan; Lee, Michael D. – Psychological Methods, 2010
The purpose of the recently proposed "p[subscript rep]" statistic is to estimate the probability of concurrence, that is, the probability that a replicate experiment yields an effect of the same sign (Killeen, 2005a). The influential journal "Psychological Science" endorses "p[subscript rep]" and recommends its use…
Descriptors: Effect Size, Evaluation Methods, Probability, Experiments
Cumming, Geoff – Psychological Methods, 2010
This comment offers three descriptions of "p[subscript rep]" that start with a frequentist account of confidence intervals, draw on R. A. Fisher's fiducial argument, and do not make Bayesian assumptions. Links are described among "p[subscript rep]," "p" values, and the probability a confidence interval will capture…
Descriptors: Replication (Evaluation), Measurement Techniques, Research Methodology, Validity
Brady, Timothy F.; Konkle, Talia; Alvarez, George A. – Journal of Experimental Psychology: General, 2009
The information that individuals can hold in working memory is quite limited, but researchers have typically studied this capacity using simple objects or letter strings with no associations between them. However, in the real world there are strong associations and regularities in the input. In an information theoretic sense, regularities…
Descriptors: Short Term Memory, Memorization, Probability, Organizations (Groups)
de la Torre, Jimmy; Song, Hao – Applied Psychological Measurement, 2009
Assessments consisting of different domains (e.g., content areas, objectives) are typically multidimensional in nature but are commonly assumed to be unidimensional for estimation purposes. The different domains of these assessments are further treated as multi-unidimensional tests for the purpose of obtaining diagnostic information. However, when…
Descriptors: Ability, Tests, Item Response Theory, Data Analysis
Roberts-Gray, Cynthia; Gingiss, Phyllis M.; Boerm, Melynda – Evaluation and Program Planning, 2007
An eight-factor survey-based Bayesian model ("Bridge-It") for assessing school capacity to implement health and education programs was tested in secondary analyses of data from 47 schools in the Texas Tobacco Prevention Initiative (TTPI). "Bridge-It" was used during the pre-implementation phase and again at mid-course of the…
Descriptors: Smoking, Bayesian Statistics, Addictive Behavior, Evaluation
McKenzie, Craig R. M.; Mikkelsen, Laurie A. – Cognitive Psychology, 2007
When participants assess the relationship between two variables, each with levels of presence and absence, the two most robust phenomena are that: (a) observing the joint presence of the variables has the largest impact on judgment and observing joint absence has the smallest impact, and (b) participants' prior beliefs about the variables'…
Descriptors: Bayesian Statistics, Statistical Analysis, Evaluation Methods
Petocz, Peter; Sowey, Eric – Teaching Statistics: An International Journal for Teachers, 2008
In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…
Descriptors: Hypothesis Testing, Statistical Inference, Statistics, Statistical Analysis
McGrath, Robert E. – Psychological Assessment, 2008
Professional psychologists are often confronted with the task of making binary decisions about individuals, such as predictions about future behavior or employee selection. Test users familiar with linear models and Bayes's theorem are likely to assume that the accuracy of decisions is consistently improved by combination of outcomes across valid…
Descriptors: Psychologists, Statistical Analysis, Regression (Statistics), Prediction

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