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Su, Hsu-Lin; Chen, Po-Hsi – Educational and Psychological Measurement, 2023
The multidimensional mixture data structure exists in many test (or inventory) conditions. Heterogeneity also relatively exists in populations. Still, some researchers are interested in deciding to which subpopulation a participant belongs according to the participant's factor pattern. Thus, in this study, we proposed three analysis procedures…
Descriptors: Data Analysis, Correlation, Classification, Factor Structure
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Raykov, Tenko; Goldammer, Philippe; Marcoulides, George A.; Li, Tatyana; Menold, Natalja – Educational and Psychological Measurement, 2018
A readily applicable procedure is discussed that allows evaluation of the discrepancy between the popular coefficient alpha and the reliability coefficient of a scale with second-order factorial structure that is frequently of relevance in empirical educational and psychological research. The approach is developed within the framework of the…
Descriptors: Test Reliability, Factor Structure, Statistical Analysis, Computation
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Gonzalez, Oscar; MacKinnon, David P. – Educational and Psychological Measurement, 2018
Statistical mediation analysis allows researchers to identify the most important mediating constructs in the causal process studied. Identifying specific mediators is especially relevant when the hypothesized mediating construct consists of multiple related facets. The general definition of the construct and its facets might relate differently to…
Descriptors: Statistical Analysis, Monte Carlo Methods, Measurement, Models
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Raykov, Tenko; Pohl, Steffi – Educational and Psychological Measurement, 2013
A method for examining common factor variance in multiple-component measuring instruments is outlined. The procedure is based on an application of the latent variable modeling methodology and is concerned with evaluating observed variance explained by a global factor and by one or more additional component-specific factors. The approach furnishes…
Descriptors: Statistical Analysis, Factor Structure, Scores, Models
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Raykov, Tenko; Pohl, Steffi – Educational and Psychological Measurement, 2013
A procedure for examining essential unidimensionality in multicomponent measuring instruments is discussed. The method is based on an application of latent variable modeling and is concerned with the extent to which a common factor for all components of a given scale accounts for their correlations. The approach provides point and interval…
Descriptors: Measures (Individuals), Statistical Analysis, Factor Structure, Correlation
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Thompson, Barry L.; Green, Samuel B.; Yang, Yanyun – Educational and Psychological Measurement, 2010
The maximal split-half coefficient is computed by calculating all possible split-half reliability estimates for a scale and then choosing the maximal value as the reliability estimate. Osburn compared the maximal split-half coefficient with 10 other internal consistency estimates of reliability and concluded that it yielded the most consistently…
Descriptors: Reliability, Computation, Simulation, Statistical Analysis
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Sass, Daniel A. – Educational and Psychological Measurement, 2010
Exploratory factor analysis (EFA) is commonly employed to evaluate the factor structure of measures with dichotomously scored items. Generally, only the estimated factor loadings are provided with no reference to significance tests, confidence intervals, and/or estimated factor loading standard errors. This simulation study assessed factor loading…
Descriptors: Intervals, Simulation, Factor Structure, Hypothesis Testing