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Wall, Melanie M.; Guo, Jia; Amemiya, Yasuo – Multivariate Behavioral Research, 2012
Mixture factor analysis is examined as a means of flexibly estimating nonnormally distributed continuous latent factors in the presence of both continuous and dichotomous observed variables. A simulation study compares mixture factor analysis with normal maximum likelihood (ML) latent factor modeling. Different results emerge for continuous versus…
Descriptors: Sample Size, Simulation, Form Classes (Languages), Diseases
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Schweizer, Karl – Multivariate Behavioral Research, 2011
The standardization of loadings gives a metric to the corresponding latent variable and thus scales the variance of this latent variable. By assigning an appropriately estimated weight to all the loadings on the same latent variable it can be achieved that the average squared loading is 1 as the result of standardization. As a consequence, there…
Descriptors: Structural Equation Models, Short Term Memory, Evaluation Methods, Comparative Analysis
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Fu, Zhi-Hui; Tao, Jian; Shi, Ning-Zhong; Zhang, Ming; Lin, Nan – Multivariate Behavioral Research, 2011
Multidimensional item response theory (MIRT) models can be applied to longitudinal educational surveys where a group of individuals are administered different tests over time with some common items. However, computational problems typically arise as the dimension of the latent variables increases. This is especially true when the latent variable…
Descriptors: Simulation, Foreign Countries, Longitudinal Studies, Item Response Theory
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Zhong, Xiaoling; Yuan, Ke-Hai – Multivariate Behavioral Research, 2011
In the structural equation modeling literature, the normal-distribution-based maximum likelihood (ML) method is most widely used, partly because the resulting estimator is claimed to be asymptotically unbiased and most efficient. However, this may not hold when data deviate from normal distribution. Outlying cases or nonnormally distributed data,…
Descriptors: Structural Equation Models, Simulation, Racial Identification, Computation
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Wang, Lijuan; Zhang, Zhiyong; McArdle, John J.; Salthouse, Timothy A. – Multivariate Behavioral Research, 2008
Score limitation at the top of a scale is commonly termed "ceiling effect." Ceiling effects can lead to serious artifactual parameter estimates in most data analysis. This study examines the consequences of ceiling effects in longitudinal data analysis and investigates several methods of dealing with ceiling effects through Monte Carlo simulations…
Descriptors: Longitudinal Studies, Data Analysis, Evaluation Methods, Monte Carlo Methods
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van Ginkel, Joost R.; van der Ark, L. Andries; Sijtsma, Klaas – Multivariate Behavioral Research, 2007
The performance of five simple multiple imputation methods for dealing with missing data were compared. In addition, random imputation and multivariate normal imputation were used as lower and upper benchmark, respectively. Test data were simulated and item scores were deleted such that they were either missing completely at random, missing at…
Descriptors: Evaluation Methods, Psychometrics, Item Response Theory, Scores
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MacCallum, Robert C.; And Others – Multivariate Behavioral Research, 1994
Alternative strategies for two-sample cross-validation of covariance structure models are described and investigated. Results of an empirical sampling study show that for tighter strategies simpler models are preferred in smaller samples, but when cross-validation is employed, a more complex model is supported even for small samples. (SLD)
Descriptors: Comparative Analysis, Evaluation Methods, Models, Research Methodology
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Lee, Sik-Yum; Song, Xin Yuan; Poon, Wai-Yin – Multivariate Behavioral Research, 2004
Various approaches using the maximum likelihood (ML) option of the LISREL program and products of indicators have been proposed to analyze structural equation models with non-linear latent effects on the basis of Kenny and Judd's formulation. Recently, some methods based on the Bayesian approach and the exact ML approaches have been developed.…
Descriptors: Comparative Analysis, Structural Equation Models, Statistical Analysis, Evaluation Methods
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McDonald, Roderick P. – Multivariate Behavioral Research, 1996
Six methods for fitting path models with weighted composites of variables replacing latent variables (of which five are easily implemented with conventional computer software) are introduced and related to "soft" modeling by Partial Least Squares. Criteria for comparing their performance are devised, and some evaluative remarks are…
Descriptors: Comparative Analysis, Computer Software, Criteria, Evaluation Methods
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Vallejo, Guillermo; Livacic-Rojas, Pablo – Multivariate Behavioral Research, 2005
This article compares two methods for analyzing small sets of repeated measures data under normal and non-normal heteroscedastic conditions: a mixed model approach with the Kenward-Roger correction and a multivariate extension of the modified Brown-Forsythe (BF) test. These procedures differ in their assumptions about the covariance structure of…
Descriptors: Computation, Multivariate Analysis, Sample Size, Matrices
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Goffin, 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
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O'Grady, Kevin E.; Medoff, Deborah R. – Multivariate Behavioral Research, 1991
A procedure for evaluating a variety of rater reliability models is presented. A multivariate linear model is used to describe and assess a set of ratings. Parameters are represented in terms of a factor analytic model, and maximum likelihood methods test the model parameters. Illustrative examples are presented. (SLD)
Descriptors: Comparative Analysis, Correlation, Equations (Mathematics), Estimation (Mathematics)
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McCrae, Robert R. – Multivariate Behavioral Research, 1993
To assess cross-observer agreement on personality profiles, an Index of Profile Agreement and an associated coefficient are proposed that take into account both the difference between the ratings and the extremes of their mean. Data from the Revised NEO Personality Inventory for 250 peer ratings/self-reports and 68 spouse ratings/self-reports…
Descriptors: Adults, Comparative Analysis, Equations (Mathematics), Evaluation Methods
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Helmes, Edward – Multivariate Behavioral Research, 1989
Objective criteria for evaluating the Eysenck Personality Inventory's internal structure are discussed. An approach based on targeted rotations and the test's scoring key is proposed as a means of providing common criteria. Data from earlier structure and test results for 195 undergraduates support the utility of 3 criteria developed. (SLD)
Descriptors: Comparative Analysis, Evaluation Criteria, Evaluation Methods, Factor Structure
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Mano, Haim – Multivariate Behavioral Research, 1991
Structure and intensity of naturally occurring and induced affect were studied with 244 university students and 1 employee in 2 studies using 2 methodological paradigms (dimensionality and classification) and 2 everyday contexts (lecture and television advertising). A circular structure of feeling was experienced during the lecture (naturally…
Descriptors: Adults, Advertising, Affective Behavior, Classification