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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
Rozeboom, William W. – Multivariate Behavioral Research, 2009
The topic of this article is the interpretation of structural equation modeling (SEM) solutions. Its purpose is to augment structural modeling's metatheoretic resources while enhancing awareness of how problematic is the causal significance of SEM-parameter solutions. Part I focuses on the nonuniqueness and consequent dubious interpretability of…
Descriptors: Structural Equation Models, Equations (Mathematics), Matrices, Probability
Peer reviewedJaccard, James; And Others – Multivariate Behavioral Research, 1990
Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)
Descriptors: Equations (Mathematics), Mathematical Models, Multiple Regression Analysis
Peer reviewedChou, Chih-Ping; Bentler, P. M. – Multivariate Behavioral Research, 1993
A new version of the standardized estimated parameter change that is invariant to the original metrics of the measured and latent variables is suggested for use in model modification. A multivariate estimated parameter change for a set of fixed parameters to be freed simultaneously is also introduced. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Mathematical Models, Multivariate Analysis
Peer reviewedMillsap, Roger E.; Meredith, William – Multivariate Behavioral Research, 1991
Mathematical relationships between three-mode component analysis and stationary component analysis are explored. Theorems are presented giving constraints that must be satisfied for equivalency between component representations provided by the methods. In general, the two approaches give mathematically distinct representations. (SLD)
Descriptors: Classification, Equations (Mathematics), Longitudinal Studies, Mathematical Models
Peer reviewedThomas, D. Roland – Multivariate Behavioral Research, 1992
The interpretation of discriminant functions as a follow-up to a significant multivariate analysis of variance is discussed. New indices are proposed that aid in identification and interpretation of the subset of response variables that contribute to a significant group discrimination. Their efficacy is compared to several commonly used…
Descriptors: Comparative Analysis, Equations (Mathematics), Mathematical Models, Multivariate Analysis
Peer reviewedBelbin, Lee; And Others – Multivariate Behavioral Research, 1992
A method for hierarchical agglomerative polythetic (multivariate) clustering, based on unweighted pair group using arithmetic averages (UPGMA) is compared with the original beta-flexible technique, a weighted average method. Reasons the flexible UPGMA strategy is recommended are discussed, focusing on the ability to recover cluster structure over…
Descriptors: Algorithms, Cluster Analysis, Comparative Analysis, Equations (Mathematics)
Peer reviewedten Berge, Jos M. F.; Zegers, Frits E. – Multivariate Behavioral Research, 1990
Arguments by J. Levin (1988) challenging the convergence properties of the Harman and Jones (1966) method of Minres factor analysis are shown to be invalid. Claims about the invalidity of a rank-one version of the Harman and Jones method are also refuted. (TJH)
Descriptors: Algorithms, Comparative Analysis, Equations (Mathematics), Factor Analysis
Peer reviewedKrolak-Schwerdt, Sabine; Eckes, Thomas – Multivariate Behavioral Research, 1992
Procedures for determining the number of clusters in a data set are explored. A proposed stopping rule, the GRAPH criterion, is compared to four stopping rules currently in use. The GRAPH criterion's mathematically attractive properties and utility in solving the number-of-clusters problem are demonstrated. (SLD)
Descriptors: Cluster Analysis, Data Collection, Equations (Mathematics), Evaluation Criteria
Peer reviewedLance, Charles E.; And Others – Multivariate Behavioral Research, 1988
Supporting the use of separate analyses of measurement and structural portions of latent or mixed manifest and latent variable models, limited information (single equation) procedures are presented for estimating structural parameters. These procedures are recommended for testing specific causal hypotheses and locating specific structural model…
Descriptors: Equations (Mathematics), Estimation (Mathematics), Mathematical Models, Monte Carlo Methods
Peer reviewedVittadini, Giorgio – Multivariate Behavioral Research, 1989
Conditions necessary and sufficient for the determination of LISREL model solutions are identified. The reasons for indeterminacy of LISREL solutions are discussed, and an index of determinacy is presented and related to the covariance matrix of latent variables. (SLD)
Descriptors: Correlation, Equations (Mathematics), Estimation (Mathematics), Evaluation Problems
Peer reviewedFornell, Claes; And Others – Multivariate Behavioral Research, 1988
This paper shows that redundancy maximization with J. K. Johansson's extension can be accomplished via a simple iterative algorithm based on H. Wold's Partial Least Squares. The model and the iterative algorithm for the least squares approach to redundancy maximization are presented. (TJH)
Descriptors: Algorithms, Equations (Mathematics), Least Squares Statistics, Mathematical Models
Peer reviewedStelzl, Ingeborg – Multivariate Behavioral Research, 1991
Criteria for factor identification in factor analysis according to J. Algina (1980) are summarized, and a procedure is presented to determine rotationally underidentified factors by adding restrictors and to carry out the rotation for old and new restrictions and in latent path analysis. Two illustrations are presented. (SLD)
Descriptors: Equations (Mathematics), Hypothesis Testing, Mathematical Models, Path Analysis
Peer reviewedBrowne, Michael W.; Du Toit, S. H. C. – Multivariate Behavioral Research, 1992
Describes a method for automated parameter estimation and testing of fit of nonstandard models for mean vectors and covariance matrices, allowing for nonlinear equality and inequality constraints on model parameters. Users need only provide subroutines to evaluate mean vector and covariance matrix according to the model and constraint functions.…
Descriptors: Analysis of Covariance, Equations (Mathematics), Estimation (Mathematics), Goodness of Fit
Peer reviewedMcDonald, Roderick P.; Hartmann, Wolfgang M. – Multivariate Behavioral Research, 1992
An algorithm for obtaining initial values for the minimization process in covariance structure analysis is developed that is more generally applicable for computing parameters connected to latent variables than the currently existing ones. The algorithm is formulated in terms of the RAM model but can be extended. (SLD)
Descriptors: Algorithms, Correlation, Equations (Mathematics), Estimation (Mathematics)

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