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Parker, Richard I.; Vannest, Kimberly J.; Davis, John L.; Clemens, Nathan H. – Journal of Special Education, 2012
Within a response to intervention model, educators increasingly use progress monitoring (PM) to support medium- to high-stakes decisions for individual students. For PM to serve these more demanding decisions requires more careful consideration of measurement error. That error should be calculated within a fixed linear regression model rather than…
Descriptors: Measurement, Computation, Response to Intervention, Regression (Statistics)
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Pae, Hye K.; Greenberg, Daphne; Morris, Robin D. – Language Assessment Quarterly, 2012
The aim of this study was to apply the Rasch model to an analysis of the psychometric properties of the Peabody Picture Vocabulary Test--III Form A (PPVT--IIIA) items with struggling adult readers. The PPVT--IIIA was administered to 229 African American adults whose isolated word reading skills were between third and fifth grades. Conformity of…
Descriptors: African Americans, Test Items, Construct Validity, Test Validity
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Webber, Douglas A. – Economics of Education Review, 2012
Using detailed individual-level data from public universities in the state of Ohio, I estimate the effect of various institutional expenditures on the probability of graduating from college. Using a competing risks regression framework, I find differential impacts of expenditure categories across student characteristics. I estimate that student…
Descriptors: Student Characteristics, Educational Finance, Measurement, Probability
Enders, Craig K. – Guilford Press, 2010
Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and…
Descriptors: Data Analysis, Error of Measurement, Research Problems, Maximum Likelihood Statistics
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Haley, M. Ryan; Johnson, Marianne F.; McGee, M. Kevin – Journal of Economic Education, 2010
The "Lake Wobegon Effect" (LWE) describes the potential measurement-error bias introduced into survey-based analyses of education issues. Although this effect potentially applies to any student-report variable, the systematic overreporting of academic achievements such as grade point average is often of preeminent concern. This concern can be…
Descriptors: Grade Point Average, Measurement Techniques, Error of Measurement, Bias
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Vaughn, Brandon K.; Wang, Qiu – Educational and Psychological Measurement, 2010
A nonparametric tree classification procedure is used to detect differential item functioning for items that are dichotomously scored. Classification trees are shown to be an alternative procedure to detect differential item functioning other than the use of traditional Mantel-Haenszel and logistic regression analysis. A nonparametric…
Descriptors: Test Bias, Classification, Nonparametric Statistics, Regression (Statistics)
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Andrich, David; Kreiner, Svend – Applied Psychological Measurement, 2010
Models of modern test theory imply statistical independence among responses, generally referred to as "local independence." One violation of local independence occurs when the response to one item governs the response to a subsequent item. Expanding on a formulation of this kind of violation as a process in the dichotomous Rasch model,…
Descriptors: Test Theory, Item Response Theory, Test Items, Correlation
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Maris, Gunter; Schmittmann, Verena D.; Borsboom, Denny – Measurement: Interdisciplinary Research and Perspectives, 2010
Test equating under the NEAT design is, at best, a necessary evil. At bottom, the procedure aims to reach a conclusion on what a tested person would have done, if he or she were administered a set of items that were in fact never administered. It is not possible to infer such a conclusion from the data, because one simply has not made the required…
Descriptors: Equated Scores, Inferences, Item Response Theory, Error of Measurement
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Cornejo, Felipe A.; Castillo, Ramon D.; Saavedra, Maria A.; Vogel, Edgar H. – Psicologica: International Journal of Methodology and Experimental Psychology, 2010
Considerable research has examined the contrasting predictions of configural and elemental associative accounts of learning. One of the simplest methods to distinguish between these approaches is the summation test, in which the associative strength of a novel compound (AB) made of two separately-trained cues (A+ and B+) is examined. The…
Descriptors: Animals, Cues, Classical Conditioning, Prediction
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Yang-Wallentin, Fan; Joreskog, Karl G.; Luo, Hao – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Ordinal variables are common in many empirical investigations in the social and behavioral sciences. Researchers often apply the maximum likelihood method to fit structural equation models to ordinal data. This assumes that the observed measures have normal distributions, which is not the case when the variables are ordinal. A better approach is…
Descriptors: Structural Equation Models, Factor Analysis, Least Squares Statistics, Computation
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Chang, Yuan-chin Ivan; Lu, Hung-Yi – Psychometrika, 2010
Item calibration is an essential issue in modern item response theory based psychological or educational testing. Due to the popularity of computerized adaptive testing, methods to efficiently calibrate new items have become more important than that in the time when paper and pencil test administration is the norm. There are many calibration…
Descriptors: Test Items, Educational Testing, Adaptive Testing, Measurement
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Andru, Peter; Botchkarev, Alexei – Journal of MultiDisciplinary Evaluation, 2011
Background: Return on investment (ROI) is one of the most popular evaluation metrics. ROI analysis (when applied correctly) is a powerful tool of evaluating existing information systems and making informed decisions on the acquisitions. However, practical use of the ROI is complicated by a number of uncertainties and controversies. The article…
Descriptors: Outcomes of Education, Information Systems, School Business Officials, Evaluation Methods
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Woods, Carol M. – Applied Psychological Measurement, 2011
Differential item functioning (DIF) occurs when an item on a test, questionnaire, or interview has different measurement properties for one group of people versus another, irrespective of true group-mean differences on the constructs being measured. This article is focused on item response theory based likelihood ratio testing for DIF (IRT-LR or…
Descriptors: Simulation, Item Response Theory, Testing, Questionnaires
Chon, Kyong Hee – ProQuest LLC, 2009
The purpose of this study was to investigate procedures for assessing model fit of IRT models for mixed format data. In this study, various IRT model combinations were fitted to data containing both dichotomous and polytomous item responses, and the suitability of the chosen model mixtures was evaluated based on a number of model fit procedures.…
Descriptors: Item Response Theory, Test Items, Goodness of Fit, Statistical Analysis
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Bollen, Kenneth A.; Davis, Walter R. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
We discuss the identification, estimation, and testing of structural equation models that have causal indicators. We first provide 2 rules of identification that are particularly helpful in models with causal indicators--the 2C emitted paths rule and the exogenous X rule. We demonstrate how these rules can help us distinguish identified from…
Descriptors: Structural Equation Models, Testing, Identification, Statistical Significance
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