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Steele, Joel S.; Ferrer, Emilio – Multivariate Behavioral Research, 2011
This article presents our response to Oud and Folmer's "Modeling Oscillation, Approximately or Exactly?" (2011), which criticizes aspects of our article, "Latent Differential Equation Modeling of Self-Regulatory and Coregulatory Affective Processes" (2011). In this response, we present a conceptual explanation of the derivative-based estimation…
Descriptors: Calculus, Responses, Simulation, Models
Liang, Jiajuan; Bentler, Peter M. – Psychometrika, 2004
Maximum likelihood is an important approach to analysis of two-level structural equation models. Different algorithms for this purpose have been available in the literature. In this paper, we present a new formulation of two-level structural equation models and develop an EM algorithm for fitting this formulation. This new formulation covers a…
Descriptors: Structural Equation Models, Mathematics, Maximum Likelihood Statistics, Goodness of Fit
Peer reviewedLee, Sik-Yum; And Others – Psychometrika, 1990
A computationally efficient three-stage estimator of thresholds and covariance structure parameters is prepared for analysis of structural equation models with polytomous variables. The method is based on partition maximum likelihood and generalized least squares estimation. An analysis of questionnaire responses of 739 young adults illustrates…
Descriptors: Equations (Mathematics), Estimation (Mathematics), Least Squares Statistics, Mathematical Models
Peer reviewedLee, Sik-Yum; And Others – Psychometrika, 1992
A two-stage approach based on the rationale of maximum likelihood and generalized least-squares methods is developed to analyze the general structural equation model for continuous and polytomous variables. Some illustrative examples and a small simulation study (50 replications) are reported. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Least Squares Statistics, Mathematical Models
Peer reviewedMeredith, William; Tisak, John – Psychometrika, 1990
A model based on latent trait theory, with maximum likelihood parameter estimates and associated asymptotic tests, is presented. Latent curve analysis is a method for representing development and is an alternative to repeated measures analysis of variance and first-order auto-regressive models. (SLD)
Descriptors: Analysis of Variance, Estimation (Mathematics), Item Response Theory, Mathematical Models

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