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Showing 1 to 15 of 411 results Save | Export
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Finch, W. Holmes – Educational and Psychological Measurement, 2020
Exploratory factor analysis (EFA) is widely used by researchers in the social sciences to characterize the latent structure underlying a set of observed indicator variables. One of the primary issues that must be resolved when conducting an EFA is determination of the number of factors to retain. There exist a large number of statistical tools…
Descriptors: Factor Analysis, Goodness of Fit, Social Sciences, Comparative Analysis
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Yesiltas, Gonca; Paek, Insu – Educational and Psychological Measurement, 2020
A log-linear model (LLM) is a well-known statistical method to examine the relationship among categorical variables. This study investigated the performance of LLM in detecting differential item functioning (DIF) for polytomously scored items via simulations where various sample sizes, ability mean differences (impact), and DIF types were…
Descriptors: Simulation, Sample Size, Item Analysis, Scores
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Murrah, William M. – Educational and Psychological Measurement, 2020
Multiple regression is often used to compare the importance of two or more predictors. When the predictors being compared are measured with error, the estimated coefficients can be biased and Type I error rates can be inflated. This study explores the impact of measurement error on comparing predictors when one is measured with error, followed by…
Descriptors: Error of Measurement, Statistical Bias, Multiple Regression Analysis, Predictor Variables
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Sideridis, Georgios D.; Tsaousis, Ioannis; Alamri, Abeer A. – Educational and Psychological Measurement, 2020
The main thesis of the present study is to use the Bayesian structural equation modeling (BSEM) methodology of establishing approximate measurement invariance (A-MI) using data from a national examination in Saudi Arabia as an alternative to not meeting strong invariance criteria. Instead, we illustrate how to account for the absence of…
Descriptors: Bayesian Statistics, Structural Equation Models, Foreign Countries, Error of Measurement
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Feuerstahler, Leah M.; Waller, Niels; MacDonald, Angus, III – Educational and Psychological Measurement, 2020
Although item response models have grown in popularity in many areas of educational and psychological assessment, there are relatively few applications of these models in experimental psychopathology. In this article, we explore the use of item response models in the context of a computerized cognitive task designed to assess visual working memory…
Descriptors: Item Response Theory, Psychopathology, Intelligence Tests, Psychological Evaluation
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Zhan, Peida – Educational and Psychological Measurement, 2020
Timely diagnostic feedback is helpful for students and teachers, enabling them to adjust their learning and teaching plans according to a current diagnosis. Motivated by the practical concern that the simultaneity estimation strategy currently adopted by longitudinal learning diagnosis models does not provide timely diagnostic feedback, this study…
Descriptors: Markov Processes, Formative Evaluation, Evaluation Methods, Feedback (Response)
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De Raadt, Alexandra; Warrens, Matthijs J.; Bosker, Roel J.; Kiers, Henk A. L. – Educational and Psychological Measurement, 2019
Cohen's kappa coefficient is commonly used for assessing agreement between classifications of two raters on a nominal scale. Three variants of Cohen's kappa that can handle missing data are presented. Data are considered missing if one or both ratings of a unit are missing. We study how well the variants estimate the kappa value for complete data…
Descriptors: Interrater Reliability, Data, Statistical Analysis, Statistical Bias
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Son, Sookyoung; Lee, Hyunjung; Jang, Yoona; Yang, Junyeong; Hong, Sehee – Educational and Psychological Measurement, 2019
The purpose of the present study is to compare nonnormal distributions (i.e., t, skew-normal, skew-t with equal skew and skew-t with unequal skew) in growth mixture models (GMMs) based on diverse conditions of a number of time points, sample sizes, and skewness for intercepts. To carry out this research, two simulation studies were conducted with…
Descriptors: Statistical Distributions, Statistical Analysis, Structural Equation Models, Comparative Analysis
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Finch, W. Holmes; Shim, Sungok Serena – Educational and Psychological Measurement, 2018
Collection and analysis of longitudinal data is an important tool in understanding growth and development over time in a whole range of human endeavors. Ideally, researchers working in the longitudinal framework are able to collect data at more than two points in time, as this will provide them with the potential for a deeper understanding of the…
Descriptors: Comparative Analysis, Computation, Time, Change
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Huang, Francis L. – Educational and Psychological Measurement, 2018
Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials…
Descriptors: Multivariate Analysis, Sampling, Statistical Inference, Data Analysis
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Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C. – Educational and Psychological Measurement, 2018
Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…
Descriptors: Error of Measurement, Testing, Scores, Models
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Komboz, Basil; Strobl, Carolin; Zeileis, Achim – Educational and Psychological Measurement, 2018
Psychometric measurement models are only valid if measurement invariance holds between test takers of different groups. Global model tests, such as the well-established likelihood ratio (LR) test, are sensitive to violations of measurement invariance, such as differential item functioning and differential step functioning. However, these…
Descriptors: Item Response Theory, Models, Tests, Measurement
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Lamprianou, Iasonas – Educational and Psychological Measurement, 2018
It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as "markers" or "judges") demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new…
Descriptors: Social Networks, Network Analysis, Comparative Analysis, Innovation
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Luo, Yong; Jiao, Hong – Educational and Psychological Measurement, 2018
Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Computer Software
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No, Unkyung; Hong, Sehee – Educational and Psychological Measurement, 2018
The purpose of the present study is to compare performances of mixture modeling approaches (i.e., one-step approach, three-step maximum-likelihood approach, three-step BCH approach, and LTB approach) based on diverse sample size conditions. To carry out this research, two simulation studies were conducted with two different models, a latent class…
Descriptors: Sample Size, Classification, Comparative Analysis, Statistical Analysis
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