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Bond, Charles F., Jr.; Kenny, David A.; Broome Elizabeth Horn; Stokes-Zoota, Juli J.; Richard, Francis D. – Multivariate Behavioral Research, 2000
Extends the Triadic Relations Model of C. Bond, E. Horn, and D. Kenny (1997) to analyze the covariances between triadic variables. Specifies a bivariate version of the model and presents estimation methods that can be used to decompose the covariance between 2 triadic variables into 33 covariance components. (Author/SLD)
Descriptors: Estimation (Mathematics), Multivariate Analysis

Chou, 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

MacCallum, Robert C.; Kim, Cheongtag; Malarkey, William B.; Kiecolt-Glaser, Janice K. – Multivariate Behavioral Research, 1997
Methods for studying relationships between patterns of change on different variables are considered, showing how the multilevel modeling framework, often used to study univariate change, can be extended to the multivariate case to yield estimates of covariances of parameters representing aspects of change for different variables. (SLD)
Descriptors: Change, Estimation (Mathematics), Item Response Theory, Mathematical Models
Computational Formulas for Multivariate Strength of Association from Approximate "F" and "X2" Tests.

Haase, Richard F. – Multivariate Behavioral Research, 1991
Computational formulas are developed for recovering measures of strength of association from approximate "F" tests and chi-square tests associated with four multivariate test statistics. The four statistics include Wilke's Lambda; Pillai's Trace "V"; Hotelling's Trace "T"; and Roy's greatest characteristic root…
Descriptors: Chi Square, Estimation (Mathematics), Mathematical Formulas, Mathematical Models

Huizenga, Hilde M.; Molenaar, Peter C. M. – Multivariate Behavioral Research, 1994
The source of an event-related brain potential (ERP) is estimated from multivariate measures of ERP on the head under several mathematical and physical constraints on the parameters of the source model. Statistical aspects of estimation are discussed, and new tests are proposed. (SLD)
Descriptors: Estimation (Mathematics), Evaluation Methods, Models, Multivariate Analysis

Wood, Phillip Karl; Games, Paul – Multivariate Behavioral Research, 1990
Conceptual rationales from five research contexts are presented, which all posit unmeasured variables that interact with observed independent variables to produce a complete model of the dependent variable. Strategies for overcoming related difficulties are outlined, including increased longitudinal assessment, oversampling of levels of…
Descriptors: Estimation (Mathematics), Longitudinal Studies, Mathematical Models, Multivariate Analysis

Kaplan, David; Wenger, R. Neill – Multivariate Behavioral Research, 1993
This article presents a didactic discussion on the role of asymptotically independent test statistics and separable hypotheses as they pertain to issues of specification error, power, and model misspecification in the covariance structure modeling framework. A small population study supports the major findings. (SLD)
Descriptors: Equations (Mathematics), Estimation (Mathematics), Hypothesis Testing, Models

MacKinnon, David P.; And Others – Multivariate Behavioral Research, 1995
Analytical solutions for point and variance estimators of the mediated effect, the ratio of mediated to direct effect, and the proportion of the total effect mediated were determined through simulation for different samples. The sample sizes needed for accuracy and stability are discussed with implications for mediated effects estimates. (SLD)
Descriptors: Equations (Mathematics), Error of Measurement, Estimation (Mathematics), Multivariate Analysis

Widaman, Keith F. – Multivariate Behavioral Research, 1993
Across conditions, differences between population parameters defined by common factor analysis and component analysis are demonstrated. Implications for data analytic and theoretical issues related to choice of analytic model are discussed. Results suggest that principal components analysis should not be used to obtain parameters reflecting latent…
Descriptors: Comparative Analysis, Equations (Mathematics), Estimation (Mathematics), Factor Analysis

Woodbury, Max A.; Manton, Kenneth G. – Multivariate Behavioral Research, 1991
An empirical Bayes-maximum likelihood estimation procedure is presented for the application of fuzzy partition models in describing high dimensional discrete response data. The model describes individuals in terms of partial membership in multiple latent categories that represent bounded discrete spaces. (SLD)
Descriptors: Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics), Mathematical Models

Kaplan, David – Multivariate Behavioral Research, 1990
A strategy for evaluating/modifying covariance structure models (CSMs) is presented. The approach uses recent developments in estimation under nonstandard conditions and unified asymptotic theory related to hypothesis testing, and it determines the extent of sample size sensitivity and specification error effects by relying on existing statistical…
Descriptors: Error of Measurement, Estimation (Mathematics), Evaluation Methods, Goodness of Fit

McArdle, J. Jack – Multivariate Behavioral Research, 1984
The many methodological contributions of Raymond B. Cattell to multivariate analysis are discussed in terms of contemporary issues in structural equation modeling. His factor analytic approach is compared with current modeling practices. A critical evaluation finds much of Cattell's work still innovative, technically advanced, and valuable to…
Descriptors: Analysis of Variance, Comparative Analysis, Estimation (Mathematics), Evaluation

Cliff, Norman; Charlin, Ventura – Multivariate Behavioral Research, 1991
Variance formulas of H. E. Daniels and M. G. Kendall (1947) are generalized to allow for the presence of ties and variance of the sample tau correlation. Applications of these generalized formulas are discussed and illustrated using data from a 1965 study of contraceptive use in 15 developing countries. (SLD)
Descriptors: Analysis of Covariance, Analysis of Variance, Contraception, Developing Nations