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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
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Cai, Li – Psychometrika, 2010
A Metropolis-Hastings Robbins-Monro (MH-RM) algorithm for high-dimensional maximum marginal likelihood exploratory item factor analysis is proposed. The sequence of estimates from the MH-RM algorithm converges with probability one to the maximum likelihood solution. Details on the computer implementation of this algorithm are provided. The…
Descriptors: Quality of Life, Factor Structure, Factor Analysis, Computation
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Templin, Jonathan L.; Henson, Robert A.; Templin, Sara E.; Roussos, Louis – Applied Psychological Measurement, 2008
Several types of parameterizations of attribute correlations in cognitive diagnosis models use the reduced reparameterized unified model. The general approach presumes an unconstrained correlation matrix with K(K - 1)/2 parameters, whereas the higher order approach postulates K parameters, imposing a unidimensional structure on the correlation…
Descriptors: Factor Structure, Identification, Correlation, Computation
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Alhija, Fadia Nasser-Abu; Wisenbaker, Joseph – Structural Equation Modeling: A Multidisciplinary Journal, 2006
A simulation study was conducted to examine the effect of item parceling on confirmatory factor analysis parameter estimates and their standard errors at different levels of sample size, number of indicators per factor, size of factor structure/pattern coefficients, magnitude of interfactor correlations, and variations in item-level data…
Descriptors: Monte Carlo Methods, Computation, Factor Analysis, Sample Size