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Solomon, Benjamin G.; Forsberg, Ole J. – School Psychology Quarterly, 2017
Bayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading…
Descriptors: Bayesian Statistics, Regression (Statistics), Least Squares Statistics, Evaluation Methods
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Hout, Michael C.; Goldinger, Stephen D.; Ferguson, Ryan W. – Journal of Experimental Psychology: General, 2013
Although traditional methods to collect similarity data (for multidimensional scaling [MDS]) are robust, they share a key shortcoming. Specifically, the possible pairwise comparisons in any set of objects grow rapidly as a function of set size. This leads to lengthy experimental protocols, or procedures that involve scaling stimulus subsets. We…
Descriptors: Visual Stimuli, Research Methodology, Problem Solving, Multidimensional Scaling
Levy, Roy – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2014
Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in…
Descriptors: Video Games, Educational Games, Bayesian Statistics, Observation
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Gardenier, George H.; Gui, Feng; Demas, James N. – Journal of Chemical Education, 2011
Complex error propagation is reduced to formula and data entry into a Mathcad worksheet or an Excel spreadsheet. The Mathcad routine uses both symbolic calculus analysis and Monte Carlo methods to propagate errors in a formula of up to four variables. Graphical output is used to clarify the contributions to the final error of each of the…
Descriptors: Monte Carlo Methods, Computer Software, Calculus, Mathematics Education
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Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas – Multivariate Behavioral Research, 2011
The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…
Descriptors: Monte Carlo Methods, Patients, Probability, Item Response Theory