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Peer reviewedTate, Richard L.; Bryant, John L. – Multivariate Behavioral Research, 1986
The shape of the response surface associated with a discriminant analysis provides insight into the value of the derived optimal discriminant variates. A procedure for the determination of "indifference regions," presented in this article, allows the assessment of the degree of flatness of the response surface for any analysis.…
Descriptors: Discriminant Analysis, Mathematical Models, Multivariate Analysis, Statistical Studies
Peer reviewedLance, Charles E. – Multivariate Behavioral Research, 1986
The logic and procedures underlying a disturbance term regression test of logical consistency for structural models are reviewed for recursive and nonrecursive designs. It is shown that in a simple three-variable, complete mediational case the test procedure is mathematically equivalent to a part correlation. (Author/LMO)
Descriptors: Correlation, Hypothesis Testing, Mathematical Models, Matrices
Peer reviewedLevin, Joseph – Multivariate Behavioral Research, 1979
Two applications of Kristof's theorem on traces of matrix products are presented in order to highlight their utility for psychometric theory and studies. (Author/JKS)
Descriptors: Mathematical Models, Matrices, Psychometrics, Statistical Analysis
Peer reviewedVelicer, Wayne F.; Fava, Joseph L. – Multivariate Behavioral Research, 1987
Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…
Descriptors: Analysis of Variance, Factor Analysis, Mathematical Models, Matrices
Peer reviewedHodapp, Volker; Wermuth, Nanny – Multivariate Behavioral Research, 1983
Decomposable models, which allow for the interdependence of structure among observable variables, are described. Each model is fully characterized by a set of conditional interdependence restrictions and can be visualized with an undirected as well as a special type of directed graph. (Author/JKS)
Descriptors: Correlation, Data Analysis, Estimation (Mathematics), Mathematical Models
Peer reviewedCollins, Linda M.; And Others – Multivariate Behavioral Research, 1986
The present study compares the performance of phi coefficients and tetrachorics along two dimensions of factor recovery in binary data. These dimensions are (1) accuracy of nontrivial factor identifications; and (2) factor structure recovery given a priori knowledge of the correct number of factors to rotate. (Author/LMO)
Descriptors: Computer Software, Factor Analysis, Factor Structure, Item Analysis
Peer reviewedHands, Stephen; Everitt, Brian – Multivariate Behavioral Research, 1987
A Monte Carlo study was made of the recovery of cluster structure in binary data by five hierarchical techniques, with a view to finding which data structure factors influenced recovery and to determining differences between clustering methods with respect to these factors. (LMO)
Descriptors: Cluster Analysis, Cluster Grouping, Goodness of Fit, Mathematical Models
Peer reviewedSpiegel, Douglas K. – Multivariate Behavioral Research, 1986
Tau, Lambda, and Kappa are measures developed for the analysis of discrete multivariate data of the type represented by stimulus response confusion matrices. The accuracy with which they may be estimated from small sample confusion matrices is investigated by Monte Carlo methods. (Author/LMO)
Descriptors: Mathematical Models, Matrices, Monte Carlo Methods, Multivariate Analysis
Peer reviewedStelzl, Ingeborg – Multivariate Behavioral Research, 1986
Since computer programs have been available for estimating and testing linear causal models, these models have been used increasingly in the behavioral sciences. This paper discusses the problem that very different causal structures may fit the same set of data equally well. (Author/LMO)
Descriptors: Computer Software, Correlation, Goodness of Fit, Mathematical Models
Peer reviewedZwick, Rebecca – Multivariate Behavioral Research, 1986
The purpose of the current study was to investigate the relative performance of the parametric, rank, and normal scores procedures when the classical assumptions were met and under violations of these assumptions. This investigation included the normal scores as well as the rank test. (LMO)
Descriptors: Hypothesis Testing, Mathematical Models, Measurement Techniques, Monte Carlo Methods
Peer reviewedOfir, Chezy; And Others – Multivariate Behavioral Research, 1987
Three frequently used response formats are compared via analysis of covariance structures. The cumulative results based on four data sets provided evidence inconsistent with previous research suggesting that these formats are interchangeable. The semantic-differential format is most preferred while in most cases the Stapel format is least…
Descriptors: Analysis of Covariance, Factor Analysis, Hypothesis Testing, Mathematical Models
Peer reviewedFarley, John U.; Reddy, Srinivas K. – Multivariate Behavioral Research, 1987
In an experiment manipulating artificial data in a factorial design, model misspecification and varying levels of error in measurement and in model structure are shown to have significant effects on LISREL parameter estimates in a modified peer influence model. (Author/LMO)
Descriptors: Analysis of Variance, Computer Simulation, Error of Measurement, Estimation (Mathematics)


