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Tenko Raykov; Christine DiStefano; Natalja Menold – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemented in particular in the popular intercept-and-slope model as well as in more general models containing it as a component, such as longitudinal…
Descriptors: Structural Equation Models, Hypothesis Testing, Longitudinal Studies, Research Methodology
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Raykov, Tenko – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…
Descriptors: Correlation, Models, Vertical Organization, Predictor Variables
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Raykov, Tenko; Penev, Spiridon – Structural Equation Modeling: A Multidisciplinary Journal, 2010
A latent variable analysis procedure for evaluation of reliability coefficients for 2-level models is outlined. The method provides point and interval estimates of group means' reliability, overall reliability of means, and conditional reliability. In addition, the approach can be used to test simple hypotheses about these parameters. The…
Descriptors: Reliability, Evaluation, Models, Intervals
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Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
A latent variable modeling approach for examining population similarities and differences in observed variable relationship and mean indexes in incomplete data sets is discussed. The method is based on the full information maximum likelihood procedure of model fitting and parameter estimation. The procedure can be employed to test group identities…
Descriptors: Models, Comparative Analysis, Groups, Maximum Likelihood Statistics