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Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S. – Multivariate Behavioral Research, 2012
A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…
Descriptors: Monte Carlo Methods, Computation, Robustness (Statistics), Structural Equation Models
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Graham, John W.; And Others – Multivariate Behavioral Research, 1996
The utility of the three-form design coupled with maximum likelihood methods for estimation of missing values was evaluated. Simulation studies demonstrate that maximum likelihood estimation and multiple imputation methods produce the most efficient and least biased estimates of variances and covariances for normally distributed and slightly…
Descriptors: Data Collection, Estimation (Mathematics), Maximum Likelihood Statistics, Research Design
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Olsson, Ulf – Multivariate Behavioral Research, 1979
The paper discusses the consequences for maximum likelihood factor analysis which may follow if the observed variables are ordinal with only a few scale steps. Results indicate that classification may lead to a substantial lack of fit of the model--an erroneous indication that more factors are needed. (Author/CTM)
Descriptors: Classification, Factor Analysis, Goodness of Fit, Maximum Likelihood Statistics
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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)