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Wang, Lijuan; Grimm, Kevin J. – Multivariate Behavioral Research, 2012
Reliabilities of the two most widely used intraindividual variability indicators, "ISD[superscript 2]" and "ISD", are derived analytically. Both are functions of the sizes of the first and second moments of true intraindividual variability, the size of the measurement error variance, and the number of assessments within a burst. For comparison,…
Descriptors: Reliability, Statistical Analysis, Measurement, Models
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Sinharay, Sandip; Puhan, Gautam; Haberman, Shelby J. – Multivariate Behavioral Research, 2010
Diagnostic scores are of increasing interest in educational testing due to their potential remedial and instructional benefit. Naturally, the number of educational tests that report diagnostic scores is on the rise, as are the number of research publications on such scores. This article provides a critical evaluation of diagnostic score reporting…
Descriptors: Educational Testing, Scores, Reports, Psychometrics
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Raykov, Tenko – Multivariate Behavioral Research, 2007
A method for point and interval estimation of change in criterion validity of multiple-component measuring instruments as a result of revision is outlined. The procedure is developed within the framework of covariance structure modeling, which complements earlier methods for testing change in composite reliability due to addition or deletion of…
Descriptors: Predictive Validity, Computation, Models, Reliability
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Wanstrom, Linda – Multivariate Behavioral Research, 2009
Second-order latent growth curve models (S. C. Duncan & Duncan, 1996; McArdle, 1988) can be used to study group differences in change in latent constructs. We give exact formulas for the covariance matrix of the parameter estimates and an algebraic expression for the estimation of slope differences. Formulas for calculations of the required sample…
Descriptors: Sample Size, Effect Size, Mathematical Formulas, Computation
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Raykov, Tenko – Multivariate Behavioral Research, 2000
Outlines a correlation structures modeling approach to the study of stability in reliability of multiple, repeatedly administered measures and illustrates the method on data from a fluid intelligence study (P. Bates and others, 1986). The method is also applicable when examining relationships between model parameters across all variables.…
Descriptors: Correlation, Models, Reliability
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Gagne, Phill; Hancock, Gregory R. – Multivariate Behavioral Research, 2006
Sample size recommendations in confirmatory factor analysis (CFA) have recently shifted away from observations per variable or per parameter toward consideration of model quality. Extending research by Marsh, Hau, Balla, and Grayson (1998), simulations were conducted to determine the extent to which CFA model convergence and parameter estimation…
Descriptors: Sample Size, Factor Analysis, Computation, Models
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Hartig, Johannes; Holzel, Britta; Moosbrugger, Helfried – Multivariate Behavioral Research, 2007
Numerous studies have shown increasing item reliabilities as an effect of the item position in personality scales. Traditionally, these context effects are analyzed based on item-total correlations. This approach neglects that trends in item reliabilities can be caused either by an increase in true score variance or by a decrease in error…
Descriptors: True Scores, Error of Measurement, Structural Equation Models, Simulation
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Rindskopf, David; Rose, Tedd – Multivariate Behavioral Research, 1988
Confirmatory factor analysis was applied to test second- and higher-order factor models in the areas of structure of abilities, allometry, and the separation of specific and error variance estimates. The estimation of validity and reliability, second-order models within factor analysis models, and the concept of discriminability were also studied.…
Descriptors: Discriminant Analysis, Error of Measurement, Estimation (Mathematics), Factor Analysis
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Whittaker, Tiffany A.; Stapleton, Laura M. – Multivariate Behavioral Research, 2006
Cudeck and Browne (1983) proposed using cross-validation as a model selection technique in structural equation modeling. The purpose of this study is to examine the performance of eight cross-validation indices under conditions not yet examined in the relevant literature, such as nonnormality and cross-validation design. The performance of each…
Descriptors: Multivariate Analysis, Selection, Structural Equation Models, Evaluation Methods