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Xia, Yan; Green, Samuel B.; Xu, Yuning; Thompson, Marilyn S. – Educational and Psychological Measurement, 2019
Past research suggests revised parallel analysis (R-PA) tends to yield relatively accurate results in determining the number of factors in exploratory factor analysis. R-PA can be interpreted as a series of hypothesis tests. At each step in the series, a null hypothesis is tested that an additional factor accounts for zero common variance among…
Descriptors: Effect Size, Factor Analysis, Hypothesis Testing, Psychometrics
Biancarosa, Gina; Kennedy, Patrick C.; Carlson, Sarah E.; Yoon, HyeonJin; Seipel, Ben; Liu, Bowen; Davison, Mark L. – Educational and Psychological Measurement, 2019
Prior research suggests that subscores from a single achievement test seldom add value over a single total score. Such scores typically correspond to subcontent areas in the total content domain, but content subdomains might not provide a sound basis for subscores. Using scores on an inferential reading comprehension test from 625 third, fourth,…
Descriptors: Scores, Scoring, Achievement Tests, Grade 3
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Olvera Astivia, Oscar L.; Kroc, Edward – Educational and Psychological Measurement, 2019
Within the context of moderated multiple regression, mean centering is recommended both to simplify the interpretation of the coefficients and to reduce the problem of multicollinearity. For almost 30 years, theoreticians and applied researchers have advocated for centering as an effective way to reduce the correlation between variables and thus…
Descriptors: Multiple Regression Analysis, Computation, Correlation, Statistical Distributions
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Marcoulides, Katerina M.; Raykov, Tenko – Educational and Psychological Measurement, 2019
A procedure that can be used to evaluate the variance inflation factors and tolerance indices in linear regression models is discussed. The method permits both point and interval estimation of these factors and indices associated with explanatory variables considered for inclusion in a regression model. The approach makes use of popular latent…
Descriptors: Regression (Statistics), Statistical Analysis, Computation, Computer Software
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Park, Minjeong; Wu, Amery D. – Educational and Psychological Measurement, 2019
Item response tree (IRTree) models are recently introduced as an approach to modeling response data from Likert-type rating scales. IRTree models are particularly useful to capture a variety of individuals' behaviors involving in item responding. This study employed IRTree models to investigate response styles, which are individuals' tendencies to…
Descriptors: Item Response Theory, Models, Likert Scales, Response Style (Tests)
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Harrison, Allyson G.; Butt, Kaitlyn; Armstrong, Irene – Educational and Psychological Measurement, 2019
There has been a marked increase in accommodation requests from students with disabilities at both the postsecondary education level and on high-stakes examinations. As such, accurate identification and quantification of normative impairment is essential for equitable provision of accommodations. Considerable diversity currently exists in methods…
Descriptors: Achievement Tests, Test Norms, Age, Instructional Program Divisions
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Wind, Stefanie A.; Guo, Wenjing – Educational and Psychological Measurement, 2019
Rater effects, or raters' tendencies to assign ratings to performances that are different from the ratings that the performances warranted, are well documented in rater-mediated assessments across a variety of disciplines. In many real-data studies of rater effects, researchers have reported that raters exhibit more than one effect, such as a…
Descriptors: Evaluators, Bias, Scoring, Data Collection
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Bürkner, Paul-Christian; Schulte, Niklas; Holling, Heinz – Educational and Psychological Measurement, 2019
Forced-choice questionnaires have been proposed to avoid common response biases typically associated with rating scale questionnaires. To overcome ipsativity issues of trait scores obtained from classical scoring approaches of forced-choice items, advanced methods from item response theory (IRT) such as the Thurstonian IRT model have been…
Descriptors: Item Response Theory, Measurement Techniques, Questionnaires, Rating Scales
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Zopluoglu, Cengiz – Educational and Psychological Measurement, 2019
Researchers frequently use machine-learning methods in many fields. In the area of detecting fraud in testing, there have been relatively few studies that have used these methods to identify potential testing fraud. In this study, a technical review of a recently developed state-of-the-art algorithm, Extreme Gradient Boosting (XGBoost), is…
Descriptors: Identification, Test Items, Deception, Cheating
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Han, Kyung T.; Dimitrov, Dimiter M.; Al-Mashary, Faisal – Educational and Psychological Measurement, 2019
The "D"-scoring method for scoring and equating tests with binary items proposed by Dimitrov offers some of the advantages of item response theory, such as item-level difficulty information and score computation that reflects the item difficulties, while retaining the merits of classical test theory such as the simplicity of number…
Descriptors: Test Construction, Scoring, Test Items, Adaptive Testing
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Kalinowski, Steven T. – Educational and Psychological Measurement, 2019
Item response theory (IRT) is a statistical paradigm for developing educational tests and assessing students. IRT, however, currently lacks an established graphical method for examining model fit for the three-parameter logistic model, the most flexible and popular IRT model in educational testing. A method is presented here to do this. The graph,…
Descriptors: Item Response Theory, Educational Assessment, Goodness of Fit, Probability
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Raykov, Tenko; Dimitrov, Dimiter M.; Marcoulides, George A.; Harrison, Michael – Educational and Psychological Measurement, 2019
This note highlights and illustrates the links between item response theory and classical test theory in the context of polytomous items. An item response modeling procedure is discussed that can be used for point and interval estimation of the individual true score on any item in a measuring instrument or item set following the popular and widely…
Descriptors: Correlation, Item Response Theory, Test Items, Scores
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Devlieger, Ines; Talloen, Wouter; Rosseel, Yves – Educational and Psychological Measurement, 2019
Factor score regression (FSR) is a popular alternative for structural equation modeling. Naively applying FSR induces bias for the estimators of the regression coefficients. Croon proposed a method to correct for this bias. Next to estimating effects without bias, interest often lies in inference of regression coefficients or in the fit of the…
Descriptors: Regression (Statistics), Computation, Goodness of Fit, Statistical Inference
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Shin, Myungho; No, Unkyung; Hong, Sehee – Educational and Psychological Measurement, 2019
The present study aims to compare the robustness under various conditions of latent class analysis mixture modeling approaches that deal with auxiliary distal outcomes. Monte Carlo simulations were employed to test the performance of four approaches recommended by previous simulation studies: maximum likelihood (ML) assuming homoskedasticity…
Descriptors: Robustness (Statistics), Multivariate Analysis, Maximum Likelihood Statistics, Statistical Distributions
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Gönülates, Emre – Educational and Psychological Measurement, 2019
This article introduces the Quality of Item Pool (QIP) Index, a novel approach to quantifying the adequacy of an item pool of a computerized adaptive test for a given set of test specifications and examinee population. This index ranges from 0 to 1, with values close to 1 indicating the item pool presents optimum items to examinees throughout the…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Error of Measurement
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