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50 Years of ERIC
50 Years of ERIC
The Education Resources Information Center (ERIC) is celebrating its 50th Birthday! First opened on May 15th, 1964 ERIC continues the long tradition of ongoing innovation and enhancement.

Learn more about the history of ERIC here. PDF icon

Showing 1 to 15 of 223 results
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Tran, Ulrich S.; Formann, Anton K. – Educational and Psychological Measurement, 2009
Parallel analysis has been shown to be suitable for dimensionality assessment in factor analysis of continuous variables. There have also been attempts to demonstrate that it may be used to uncover the factorial structure of binary variables conforming to the unidimensional normal ogive model. This article provides both theoretical and empirical…
Descriptors: Simulation, Factor Analysis, Correlation, Evaluation Methods
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Liu, Yan; Zumbo, Bruno D. – Educational and Psychological Measurement, 2007
The impact of outliers on Cronbach's coefficient [alpha] has not been documented in the psychometric or statistical literature. This is an important gap because coefficient [alpha] is the most widely used measurement statistic in all of the social, educational, and health sciences. The impact of outliers on coefficient [alpha] is investigated for…
Descriptors: Psychometrics, Computation, Reliability, Monte Carlo Methods
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Wilcox, Rand R. – Educational and Psychological Measurement, 2006
Consider the nonparametric regression model Y = m(X)+ [tau](X)[epsilon], where X and [epsilon] are independent random variables, [epsilon] has a median of zero and variance [sigma][squared], [tau] is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated…
Descriptors: Nonparametric Statistics, Mathematical Models, Regression (Statistics), Probability
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Graham, James M. – Educational and Psychological Measurement, 2006
Coefficient alpha, the most commonly used estimate of internal consistency, is often considered a lower bound estimate of reliability, though the extent of its underestimation is not typically known. Many researchers are unaware that coefficient alpha is based on the essentially tau-equivalent measurement model. It is the violation of the…
Descriptors: Models, Test Theory, Reliability, Structural Equation Models
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Rupp, Andre A.; Zumbo, Bruno D. – Educational and Psychological Measurement, 2004
Based on seminal work by Lord and Hambleton, Swaminathan, and Rogers, this article is an analytical, graphical, and conceptual reminder that item response theory (IRT) parameter invariance only holds for perfect model fit in multiple populations or across multiple conditions and is thus an ideal state. In practice, one attempts to quantify the…
Descriptors: Correlation, Item Response Theory, Statistical Analysis, Evaluation Methods
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Enders, Craig K. – Educational and Psychological Measurement, 2001
Examined the performance of a recently available full information maximum likelihood (FIML) estimator in a multiple regression model with missing data using Monte Carlo simulation and considering the effects of four independent variables. Results indicate that FIML estimation was superior to that of three ad hoc techniques, with less bias and less…
Descriptors: Estimation (Mathematics), Mathematical Models, Maximum Likelihood Statistics, Monte Carlo Methods
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van Prooijen, Jan-Willem; van der Kloot, Willem A. – Educational and Psychological Measurement, 2001
Assessed the extent to which results in exploratory factor analysis (EFA) studies can be replicated by confirmatory factor analysis in the same sample. Used 10 factor structures drawn from the literature. Results show that confirmatory factor models in which all low EFA pattern coefficients were fixed to zero fitted especially poorly. (SLD)
Descriptors: Factor Structure, Mathematical Models
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Ferrando, Pere J.; Lorenzo-Seva, Urbano – Educational and Psychological Measurement, 2001
Describes a Windows program for checking the suitability of unidimensional logistic item response models for binary and ordered polytomous responses with respect to a given set of data. The program is based on predicting the observed test score distributions from the item characteristic curves. (SLD)
Descriptors: Computer Software, Item Response Theory, Mathematical Models, Prediction
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Tate, Richard – Educational and Psychological Measurement, 2000
Investigated the robustness of the group-level polytomous Item Response Theory model to violations of assumptions of school-level normality and within-school normality and constant variance with eight large simulated case samples. Discusses the precision obtained in estimating school ability. (SLD)
Descriptors: Ability, Case Studies, Elementary Secondary Education, Estimation (Mathematics)
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Huitema, Bradley E.; McKean, Joseph W. – Educational and Psychological Measurement, 2000
Presents examples of egregious errors of interpretation in time-series intervention models and makes recommendations regarding the correct specification of the design matrix. Discusses the profound effects of variants of the slope change variable in the design matrix. (SLD)
Descriptors: Intervention, Mathematical Models, Research Design
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Fan, Xitao; Wang, Lin – Educational and Psychological Measurement, 1998
In this Monte Carlo study, the effects of four factors on structural equation modeling (SEM) fit indices and parameter estimates were investigated. The 14,400 samples generated were fitted to 3 SEM models with different degrees of model misspecification. Effects of data nonnormality, estimation method, and sample size are noted. (SLD)
Descriptors: Estimation (Mathematics), Goodness of Fit, Mathematical Models, Monte Carlo Methods
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Cramer, Kenneth M. – Educational and Psychological Measurement, 1998
Whether the one- or two-factor Wechsler or weighted sum scores (WSS) structural models adequately fit the Wechsler Intelligence Scale for Children III (WISC-III) covariance matrices was studied with samples of 2200 and 1118 children from previous studies. Both the WSS and supplemented models provided better fit than Wechsler's model but still…
Descriptors: Comparative Analysis, Factor Structure, Goodness of Fit, Intelligence
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Huberty, Carl J.; Lowman, Laureen L. – Educational and Psychological Measurement, 1997
Predictive discriminant analysis and descriptive discriminant analysis are described, and the use of three popular statistical packages to obtain computational results for each type of discriminant analysis is reviewed. Results from two Biomedical Computer Program (BMDP), four Statistical Analysis System, and two Statistical Package for the Social…
Descriptors: Computer Software, Discriminant Analysis, Mathematical Models, Prediction
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Bedeian, Arthur G.; Day, David V.; Kelloway, E. Kevin – Educational and Psychological Measurement, 1997
Methods by which structural models correct for the effects of attenuation due to measurement error are reviewed, and implications of such disattenuation for interpreting the results of structural equation models are considered. Recommendations are made for improving the practice of disattenuation, and caution is urged in drawing inferences based…
Descriptors: Error of Measurement, Estimation (Mathematics), Mathematical Models, Statistical Inference
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Thompson, Bruce – Educational and Psychological Measurement, 1997
A general linear model framework is used to suggest that structure coefficients ought to be interpreted in structural equation modeling confirmatory factor analysis (CFA) studies in which factors are correlated. Two heuristic data sets make the discussion concrete, and two additional studies illustrate the benefits of CFA structure coefficients.…
Descriptors: Factor Analysis, Mathematical Models, Structural Equation Models
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