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Vallejo, G.; Fernandez, M. P.; Livacic-Rojas, P. E.; Tuero-Herrero, E. – Multivariate Behavioral Research, 2011
Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…
Descriptors: Personality Problems, Psychosis, Prevention, Patients
Peer reviewedTimm, Neil H. – Multivariate Behavioral Research, 1995
The finite intersection test (FIT) developed by P. K. Krishnaiah (1964, 1965) is discussed and compared with more familiar methods for simultaneous inference. How the FIT can be used to analyze differences among all means for both univariate and multivariate experimental designs is explained. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Multivariate Analysis, Statistical Inference
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 reviewedKaplan, 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
Peer reviewedTimm, Neil H. – Multivariate Behavioral Research, 1999
Investigates the equality of "p" correlated effect sizes for "k" independent studies in which treatment and control groups are compared using Hotelling's "T" statistic. Illustrates the procedure and discusses the importance of sample size. (SLD)
Descriptors: Comparative Analysis, Control Groups, Correlation, Effect Size
Peer reviewedMacKinnon, 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
Peer reviewedWidaman, 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
Peer reviewedWoodbury, 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
Peer reviewedGoffin, Richard D. – Multivariate Behavioral Research, 1993
Two recent indices of fit, the Relative Noncentrality Index (RNI) (R. P. McDonald and H. W. Marsh, 1990) and the Comparative Fit Index (P. M. Bentler, 1990), are shown to be algebraically equivalent in most applications, although one condition in which the RNI may be advantageous for model comparison is identified. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Evaluation Methods, Goodness of Fit
Peer reviewedBaker, Laura A. – Multivariate Behavioral Research, 1989
A bivariate generalization of the genotype-environment covariation (GEC) is presented. A multivariate procedure for detecting univariate and bivariate GEC is also described and illustrated via a study of 136 adopted and 125 non-adopted 4-year-old children. (SLD)
Descriptors: Adopted Children, Analysis of Covariance, Cognitive Ability, Comparative Analysis
Peer reviewedCliff, 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
Peer reviewedTang, K. Linda; Algina, James – Multivariate Behavioral Research, 1993
Type I error rates of four multivariate tests (Pilai-Bartlett trace, Johansen's test, James' first-order test, and James' second-order test) were compared for heterogeneous covariance matrices in 360 simulated experiments. The superior performance of Johansen's test and James' second-order test is discussed. (SLD)
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Equations (Mathematics)

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