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Testing Specific Hypotheses Concerning Latent Group Differences in Multi-group Covariance Structure Analysis with Structured Means.
Peer reviewed Peer reviewed
Dolan, Conor V.; Molenaar, Peter C. M. – Multivariate Behavioral Research, 1994
In multigroup covariance structure analysis with structured means, the traditional latent selection model is formulated as a special case of phenotypic selection. Illustrations with real and simulated data demonstrate how one can test specific hypotheses concerning selection on latent variables. (SLD)
Descriptors: Analysis of Covariance, Group Membership, Hypothesis Testing, Selection
Factor Recovery in Binary Data Sets: A Simulation.
Peer reviewed Peer reviewed
Collins, 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
A Factorial Evaluation of Effects of Model Specification and Error on Parameter Estimation in a Structural Equation Model.
Peer reviewed Peer reviewed
Farley, 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)
Performance of Four Multivariate Tests under Variance-Covariance Heteroscedasticity.
Peer reviewed Peer reviewed
Tang, 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)