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Raykov, Tenko; Anthony, James C.; Menold, Natalja – Educational and Psychological Measurement, 2023
The population relationship between coefficient alpha and scale reliability is studied in the widely used setting of unidimensional multicomponent measuring instruments. It is demonstrated that for any set of component loadings on the common factor, regardless of the extent of their inequality, the discrepancy between alpha and reliability can be…
Descriptors: Correlation, Evaluation Research, Reliability, Measurement Techniques
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Akaeze, Hope O.; Lawrence, Frank R.; Wu, Jamie Heng-Chieh – Educational and Psychological Measurement, 2023
Multidimensionality and hierarchical data structure are common in assessment data. These design features, if not accounted for, can threaten the validity of the results and inferences generated from factor analysis, a method frequently employed to assess test dimensionality. In this article, we describe and demonstrate the application of the…
Descriptors: Measures (Individuals), Multidimensional Scaling, Tests, Hierarchical Linear Modeling
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Raykov, Tenko; Pusic, Martin – Educational and Psychological Measurement, 2023
This note is concerned with evaluation of location parameters for polytomous items in multiple-component measuring instruments. A point and interval estimation procedure for these parameters is outlined that is developed within the framework of latent variable modeling. The method permits educational, behavioral, biomedical, and marketing…
Descriptors: Item Analysis, Measurement Techniques, Computer Software, Intervals
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Goretzko, David; Heumann, Christian; Bühner, Markus – Educational and Psychological Measurement, 2020
Exploratory factor analysis is a statistical method commonly used in psychological research to investigate latent variables and to develop questionnaires. Although such self-report questionnaires are prone to missing values, there is not much literature on this topic with regard to exploratory factor analysis--and especially the process of factor…
Descriptors: Factor Analysis, Data Analysis, Research Methodology, Psychological Studies
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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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Li, Wei; Konstantopoulos, Spyros – Educational and Psychological Measurement, 2017
Field experiments in education frequently assign entire groups such as schools to treatment or control conditions. These experiments incorporate sometimes a longitudinal component where for example students are followed over time to assess differences in the average rate of linear change, or rate of acceleration. In this study, we provide methods…
Descriptors: Educational Experiments, Field Studies, Models, Randomized Controlled Trials
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Raykov, Tenko; Marcoulides, George A.; Tong, Bing – Educational and Psychological Measurement, 2016
A latent variable modeling procedure is discussed that can be used to test if two or more homogeneous multicomponent instruments with distinct components are measuring the same underlying construct. The method is widely applicable in scale construction and development research and can also be of special interest in construct validation studies.…
Descriptors: Models, Statistical Analysis, Measurement Techniques, Factor Analysis
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Devlieger, Ines; Mayer, Axel; Rosseel, Yves – Educational and Psychological Measurement, 2016
In this article, an overview is given of four methods to perform factor score regression (FSR), namely regression FSR, Bartlett FSR, the bias avoiding method of Skrondal and Laake, and the bias correcting method of Croon. The bias correcting method is extended to include a reliable standard error. The four methods are compared with each other and…
Descriptors: Regression (Statistics), Comparative Analysis, Structural Equation Models, Monte Carlo Methods
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Cousineau, Denis; Laurencelle, Louis – Educational and Psychological Measurement, 2015
Existing tests of interrater agreements have high statistical power; however, they lack specificity. If the ratings of the two raters do not show agreement but are not random, the current tests, some of which are based on Cohen's kappa, will often reject the null hypothesis, leading to the wrong conclusion that agreement is present. A new test of…
Descriptors: Interrater Reliability, Monte Carlo Methods, Measurement Techniques, Accuracy
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Bishara, Anthony J.; Hittner, James B. – Educational and Psychological Measurement, 2015
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
Descriptors: Research Methodology, Monte Carlo Methods, Correlation, Simulation
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French, Brian F.; Finch, W. Holmes – Educational and Psychological Measurement, 2013
Multilevel data structures are ubiquitous in the assessment of differential item functioning (DIF), particularly in large-scale testing programs. There are a handful of DIF procures for researchers to select from that appropriately account for multilevel data structures. However, little, if any, work has been completed to extend a popular DIF…
Descriptors: Test Bias, Statistical Analysis, Comparative Analysis, Correlation
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Kim, Eun Sook; Yoon, Myeongsun; Lee, Taehun – Educational and Psychological Measurement, 2012
Multiple-indicators multiple-causes (MIMIC) modeling is often used to test a latent group mean difference while assuming the equivalence of factor loadings and intercepts over groups. However, this study demonstrated that MIMIC was insensitive to the presence of factor loading noninvariance, which implies that factor loading invariance should be…
Descriptors: Test Items, Simulation, Testing, Statistical Analysis
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Cho, Sun-Joo; Li, Feiming; Bandalos, Deborah – Educational and Psychological Measurement, 2009
The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…
Descriptors: Correlation, Evaluation Methods, Data Analysis, Matrices
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Wilcox, Rand R. – Educational and Psychological Measurement, 2006
For two random variables, X and Y, let D = X - Y, and let theta[subscript x], theta[subscript y], and theta[subscript d] be the corresponding medians. It is known that the Wilcoxon-Mann-Whitney test and its modern extensions do not test H[subscript o] : theta[subscript x] = theta[subscript y], but rather, they test H[subscript o] : theta[subscript…
Descriptors: Scores, Inferences, Comparative Analysis, Statistical Analysis
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Wilcox, Rand R. – Educational and Psychological Measurement, 2005
It is known that nonnormality, a heteroscedastic error term, or a nonlinear association can create serious practical problems when using the conventional analysis of covariance (ANCOVA) method. This article describes a simple ANCOVA method that allows heteroscedasticity, nonnormality, nonlinearity, and multiple covariates. When standard…
Descriptors: Statistical Analysis, Error of Measurement, Measurement Techniques
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