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Fu, Yuanshu; Wen, Zhonglin; Wang, Yang – Educational and Psychological Measurement, 2022

Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is…

Descriptors: Comparative Analysis, Structural Equation Models, Factor Analysis, Reliability

Edwards, Ashley A.; Joyner, Keanan J.; Schatschneider, Christopher – Educational and Psychological Measurement, 2021

The accuracy of certain internal consistency estimators have been questioned in recent years. The present study tests the accuracy of six reliability estimators (Cronbach's alpha, omega, omega hierarchical, Revelle's omega, and greatest lower bound) in 140 simulated conditions of unidimensional continuous data with uncorrelated errors with varying…

Descriptors: Reliability, Computation, Accuracy, Sample Size

Raymond, Mark R.; Jiang, Zhehan – Educational and Psychological Measurement, 2020

Conventional methods for evaluating the utility of subscores rely on traditional indices of reliability and on correlations among subscores. One limitation of correlational methods is that they do not explicitly consider variation in subtest means. An exception is an index of score profile reliability designated as [G], which quantifies the ratio…

Descriptors: Generalizability Theory, Multivariate Analysis, Scores, Reliability

Jaki, Thomas; Kim, Minjung; Lamont, Andrea; George, Melissa; Chang, Chi; Feaster, Daniel; Van Horn, M. Lee – Educational and Psychological Measurement, 2019

Regression mixture models are a statistical approach used for estimating heterogeneity in effects. This study investigates the impact of sample size on regression mixture's ability to produce "stable" results. Monte Carlo simulations and analysis of resamples from an application data set were used to illustrate the types of problems that…

Descriptors: Sample Size, Computation, Regression (Statistics), Reliability

Ferrando, Pere J.; Lorenzo-Seva, Urbano – Educational and Psychological Measurement, 2019

Measures initially designed to be single-trait often yield data that are compatible with both an essentially unidimensional factor-analysis (FA) solution and a correlated-factors solution. For these cases, this article proposes an approach aimed at providing information for deciding which of the two solutions is the most appropriate and useful.…

Descriptors: Factor Analysis, Computation, Reliability, Goodness of Fit

Briggs, Derek C.; Alzen, Jessica L. – Educational and Psychological Measurement, 2019

Observation protocol scores are commonly used as status measures to support inferences about teacher practices. When multiple observations are collected for the same teacher over the course of a year, some portion of a teacher's score on each occasion may be attributable to the rater, lesson, and the time of year of the observation. All three of…

Descriptors: Observation, Inferences, Generalizability Theory, Scores

Nicewander, W. Alan – Educational and Psychological Measurement, 2018

Spearman's correction for attenuation (measurement error) corrects a correlation coefficient for measurement errors in either-or-both of two variables, and follows from the assumptions of classical test theory. Spearman's equation removes all measurement error from a correlation coefficient which translates into "increasing the reliability of…

Descriptors: Error of Measurement, Correlation, Sample Size, Computation

Trafimow, David – Educational and Psychological Measurement, 2018

Because error variance alternatively can be considered to be the sum of systematic variance associated with unknown variables and randomness, a tripartite assumption is proposed that total variance in the dependent variable can be partitioned into three variance components. These are variance in the dependent variable that is explained by the…

Descriptors: Statistical Analysis, Correlation, Experiments, Effect Size

Raykov, Tenko; Marcoulides, George A.; Li, Tenglong – Educational and Psychological Measurement, 2018

This note extends the results in the 2016 article by Raykov, Marcoulides, and Li to the case of correlated errors in a set of observed measures subjected to principal component analysis. It is shown that when at least two measures are fallible, the probability is zero for any principal component--and in particular for the first principal…

Descriptors: Factor Analysis, Error of Measurement, Correlation, Reliability

Deng, Lifang; Chan, Wai – Educational and Psychological Measurement, 2017

Reliable measurements are key to social science research. Multiple measures of reliability of the total score have been developed, including coefficient alpha, coefficient omega, the greatest lower bound reliability, and others. Among these, the coefficient alpha has been most widely used, and it is reported in nearly every study involving the…

Descriptors: Reliability, Statistical Analysis, Computation, Differences

Liu, Ren; Huggins-Manley, Anne Corinne; Bradshaw, Laine – Educational and Psychological Measurement, 2017

There is an increasing demand for assessments that can provide more fine-grained information about examinees. In response to the demand, diagnostic measurement provides students with feedback on their strengths and weaknesses on specific skills by classifying them into mastery or nonmastery attribute categories. These attributes often form a…

Descriptors: Matrices, Classification, Accuracy, Diagnostic Tests

Raykov, Tenko; Marcoulides, George A.; Li, Tenglong – Educational and Psychological Measurement, 2017

The measurement error in principal components extracted from a set of fallible measures is discussed and evaluated. It is shown that as long as one or more measures in a given set of observed variables contains error of measurement, so also does any principal component obtained from the set. The error variance in any principal component is shown…

Descriptors: Error of Measurement, Factor Analysis, Research Methodology, Psychometrics

Plieninger, Hansjörg – Educational and Psychological Measurement, 2017

Even though there is an increasing interest in response styles, the field lacks a systematic investigation of the bias that response styles potentially cause. Therefore, a simulation was carried out to study this phenomenon with a focus on applied settings (reliability, validity, scale scores). The influence of acquiescence and extreme response…

Descriptors: Response Style (Tests), Test Bias, Item Response Theory, Correlation

Cho, Sun-Joo; Preacher, Kristopher J. – Educational and Psychological Measurement, 2016

Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

Descriptors: Error of Measurement, Error Correction, Multivariate Analysis, Hierarchical Linear Modeling

Attali, Yigal; Laitusis, Cara; Stone, Elizabeth – Educational and Psychological Measurement, 2016

There are many reasons to believe that open-ended (OE) and multiple-choice (MC) items elicit different cognitive demands of students. However, empirical evidence that supports this view is lacking. In this study, we investigated the reactions of test takers to an interactive assessment with immediate feedback and answer-revision opportunities for…

Descriptors: Test Items, Questioning Techniques, Differences, Student Reaction