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Conger, Anthony J. – Educational and Psychological Measurement, 2017
Drawing parallels to classical test theory, this article clarifies the difference between rater accuracy and reliability and demonstrates how category marginal frequencies affect rater agreement and Cohen's kappa. Category assignment paradigms are developed: comparing raters to a standard (index) versus comparing two raters to one another…
Descriptors: Interrater Reliability, Evaluators, Accuracy, Statistical Analysis
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Cousineau, Denis; Laurencelle, Louis – Educational and Psychological Measurement, 2017
Assessing global interrater agreement is difficult as most published indices are affected by the presence of mixtures of agreements and disagreements. A previously proposed method was shown to be specifically sensitive to global agreement, excluding mixtures, but also negatively biased. Here, we propose two alternatives in an attempt to find what…
Descriptors: Interrater Reliability, Evaluation Methods, Statistical Bias, Accuracy
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DiStefano, Christine; McDaniel, Heather L.; Zhang, Liyun; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2019
A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted least squares to determine how varying sample size, number of ordered categories, and…
Descriptors: Factor Analysis, Effect Size, Data, Sample Size
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Park, Ryoungsun; Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G. – Educational and Psychological Measurement, 2017
The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…
Descriptors: Testing, Performance, Prediction, Error of Measurement
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Nugent, William Robert; Moore, Matthew; Story, Erin – Educational and Psychological Measurement, 2015
The standardized mean difference (SMD) is perhaps the most important meta-analytic effect size. It is typically used to represent the difference between treatment and control population means in treatment efficacy research. It is also used to represent differences between populations with different characteristics, such as persons who are…
Descriptors: Error of Measurement, Error Correction, Predictor Variables, Monte Carlo Methods
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Park, Jungkyu; Yu, Hsiu-Ting – Educational and Psychological Measurement, 2016
The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…
Descriptors: Hierarchical Linear Modeling, Nonparametric Statistics, Data Analysis, Simulation
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Gómez-Benito, Juana; Hidalgo, Maria Dolores; Zumbo, Bruno D. – Educational and Psychological Measurement, 2013
The objective of this article was to find an optimal decision rule for identifying polytomous items with large or moderate amounts of differential functioning. The effectiveness of combining statistical tests with effect size measures was assessed using logistic discriminant function analysis and two effect size measures: R[superscript 2] and…
Descriptors: Item Analysis, Test Items, Effect Size, Statistical Analysis
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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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Brennan, Robert L.; Prediger, Dale J. – Educational and Psychological Measurement, 1981
This paper considers some appropriate and inappropriate uses of coefficient kappa and alternative kappa-like statistics. Discussion is restricted to the descriptive characteristics of these statistics for measuring agreement with categorical data in studies of reliability and validity. (Author)
Descriptors: Classification, Error of Measurement, Mathematical Models, Test Reliability
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Cahan, Sorel; Cohen, Nora – Educational and Psychological Measurement, 1990
A solution is offered to problems associated with the inequality in the manipulability of probabilities of classification errors of masters versus nonmasters, based on competency test results. Eschewing the typical arbitrary establishment of observed-score standards below 100 percent, the solution incorporates a self-correction of wrong answers.…
Descriptors: Classification, Error of Measurement, Mastery Tests, Minimum Competency Testing