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Showing 1 to 15 of 405 results Save | Export
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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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Zijlmans, Eva A. O.; Tijmstra, Jesper; van der Ark, L. Andries; Sijtsma, Klaas – Educational and Psychological Measurement, 2018
Reliability is usually estimated for a total score, but it can also be estimated for item scores. Item-score reliability can be useful to assess the repeatability of an individual item score in a group. Three methods to estimate item-score reliability are discussed, known as method MS, method [lambda][subscript 6], and method CA. The item-score…
Descriptors: Test Items, Test Reliability, Correlation, Comparative Analysis
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Fu, Yuanshu; Wen, Zhonglin; Wang, Yang – Educational and Psychological Measurement, 2018
The maximal reliability of a congeneric measure is achieved by weighting item scores to form the optimal linear combination as the total score; it is never lower than the composite reliability of the measure when measurement errors are uncorrelated. The statistical method that renders maximal reliability would also lead to maximal criterion…
Descriptors: Test Reliability, Test Validity, Comparative Analysis, Attitude Measures
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Kim, Eun Sook; Wang, Yan; Kiefer, Sarah M. – Educational and Psychological Measurement, 2018
Studies comparing groups that are at different levels of multilevel data (namely, cross-level groups) using the same measure are not unusual such as student and teacher agreement in education or congruence between patient and physician perceptions in health research. Although establishing measurement invariance (MI) between these groups is…
Descriptors: Measurement, Grouping (Instructional Purposes), Comparative Analysis, Factor Analysis
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Cain, Meghan K.; Zhang, Zhiyong; Bergeman, C. S. – Educational and Psychological Measurement, 2018
This article serves as a practical guide to mediation design and analysis by evaluating the ability of mediation models to detect a significant mediation effect using limited data. The cross-sectional mediation model, which has been shown to be biased when the mediation is happening over time, is compared with longitudinal mediation models:…
Descriptors: Mediation Theory, Case Studies, Longitudinal Studies, Measurement Techniques
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Green, Samuel; Xu, Yuning; Thompson, Marilyn S. – Educational and Psychological Measurement, 2018
Parallel analysis (PA) assesses the number of factors in exploratory factor analysis. Traditionally PA compares the eigenvalues for a sample correlation matrix with the eigenvalues for correlation matrices for 100 comparison datasets generated such that the variables are independent, but this approach uses the wrong reference distribution. The…
Descriptors: Factor Analysis, Accuracy, Statistical Distributions, Comparative Analysis
Koziol, Natalie A.; Bovaird, James A. – Educational and Psychological Measurement, 2018
Evaluations of measurement invariance provide essential construct validity evidence--a prerequisite for seeking meaning in psychological and educational research and ensuring fair testing procedures in high-stakes settings. However, the quality of such evidence is partly dependent on the validity of the resulting statistical conclusions. Type I or…
Descriptors: Computation, Tests, Error of Measurement, Comparative Analysis
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