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Robles, Jaime – Structural Equation Modeling, 1996
A theoretical and philosophical revision of the concept of fit in structural equation modeling and its relation to a confirmation bias is developed. The neutral character of fit indexes regarding this issue is argued, concluding that protection against confirmation bias relies on model modification strategy and scientist behavior. (SLD)
Descriptors: Causal Models, Goodness of Fit, Mathematical Models, Statistical Bias
Peer reviewed Peer reviewed
Brown, Roger L. – Structural Equation Modeling, 1997
Reviews the use of structural equation modeling for providing an overall assessment of mediation, the mechanism that accounts for the relation between the predictor and the criterion. A strategy for supplemental details is presented that measures the magnitude of mediational effects. (SLD)
Descriptors: Computer Software, Mathematical Models, Predictor Variables, Structural Equation Models
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van den Putte, Bas; Hoogstraten, Johan – Structural Equation Modeling, 1997
Problems found in the application of structural equation modeling to the theory of reasoned action are explored, and an alternative model specification is proposed that improves the fit of the data while leaving intact the structural part of the model being tested. Problems and the proposed alternative are illustrated. (SLD)
Descriptors: Goodness of Fit, Mathematical Models, Research Methodology, Structural Equation Models
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Gerbing, David W.; Hamilton, Janet G. – Structural Equation Modeling, 1996
A Monte Carlo study evaluated the effectiveness of different factor analysis extraction and rotation methods for identifying the known population multiple-indicator measurement model. Results demonstrate that exploratory factor analysis can contribute to a useful heuristic strategy for model specification prior to cross-validation with…
Descriptors: Heuristics, Mathematical Models, Measurement Techniques, Monte Carlo Methods
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Kaplan, David; Elliott, Pamela R. – Structural Equation Modeling, 1997
A didactic example is presented of the application of new developments in structural equation modeling that allow for the modeling of multilevel data. The method, a synthesis of methods developed by B. Muthen, is applied to the problem of validating indicators of science education quality in the United States. (SLD)
Descriptors: Data Analysis, Educational Quality, Mathematical Models, Organization
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Mueller, Ralph O. – Structural Equation Modeling, 1997
Basic philosophical and statistical issues in structural equation modeling (SEM) are reviewed, including model conceptualization, identification, and parameter estimation and data-model-fit assessment and model modification. These issues should be addressed before the researcher uses any of the new generation of SEM software. (SLD)
Descriptors: Computer Software, Estimation (Mathematics), Goodness of Fit, Identification
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Mulaik, Stanley A.; Quartetti, Douglas A. – Structural Equation Modeling, 1997
The Schmid-Leiman (J. Schmid and J. M. Leiman, 1957) decomposition of a hierarchical factor model converts the model to a constrained case of a bifactor model with orthogonal common factors that is equivalent to the hierarchical model. This article discusses the equivalence of the hierarchical and bifactor models. (Author/SLD)
Descriptors: Factor Analysis, Factor Structure, Mathematical Models
Peer reviewed Peer reviewed
Schumacker, Randall E. – Structural Equation Modeling, 2002
Used simulation to study two different approaches to latent variable interaction modeling with continuous observed variables: (1) a LISREL 8.30 program and (2) data analysis through PRELIS2 and SIMPLIS programs. Results show that parameter estimation was similar but standard errors were different. Discusses differences in ease of implementation.…
Descriptors: Error of Measurement, Interaction, Mathematical Models
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Hancock, Gregory R.; Kuo, Wen-Ling; Lawrence, Frank R. – Structural Equation Modeling, 2001
Using higher order factor models, this article illustrates latent curve analysis for the purpose of modeling longitudinal change directly in a latent construct. Provides examples with simultaneous estimation of covariance and mean structures for a single-group and two-group structure. (SLD)
Descriptors: Analysis of Covariance, Factor Analysis, Mathematical Models
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Rovine, Michael J.; Molenaar, Peter C. M. – Structural Equation Modeling, 1998
Presents a LISREL model for the estimation of the repeated measures analysis of variance (ANOVA) with a patterned covariance matrix. The model is demonstrated for a 5 x 2 (Time x Group) ANOVA in which the data are assumed to be serially correlated. Similarities with the Statistical Analysis System PROC MIXED model are discussed. (SLD)
Descriptors: Analysis of Covariance, Correlation, Estimation (Mathematics), Mathematical Models
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Cheung, Mike W. -L.; Chan, Wai – Structural Equation Modeling, 2002
Defines a mathematical model of uniform response bias (URB) and proposes ipsative measures to minimize the effect of URB in multigroup confirmatory factor analysis. Illustrates the method using real data from the Chinese Personality Assessment Inventory for 2 groups of sample sizes 793 and 792 adults. (SLD)
Descriptors: Adults, Foreign Countries, Mathematical Models, Personality Assessment
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Bacon, Donald R. – Structural Equation Modeling, 2001
Evaluated the performance of several alternative cluster analytic approaches to initial model specification using population parameter analyses and a Monte Carlo simulation. Of the six cluster approaches evaluated, the one using the correlations of item correlations as a proximity metric and average linking as a clustering algorithm performed the…
Descriptors: Algorithms, Cluster Analysis, Correlation, Mathematical Models
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Green, Samuel B.; And Others – Structural Equation Modeling, 1997
A study of the effect of the number of item response categories on chi-square statistics for confirmatory factor analysis indicates that the chi-square statistic for evaluating a single-factor model is most inflated for two-category responses and becomes less inflated as the number of categories increases. (SLD)
Descriptors: Chi Square, Classification, Goodness of Fit, Item Response Theory
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Gribbons, Barry C.; Hocevar, Dennis – Structural Equation Modeling, 1998
The effects of levels of aggregation on measures of goodness of fit and higher order parameter estimates obtained from confirmatory factor analysis (CFA) were investigated using three indexes of fit and data on the academic self-concept of 270 undergraduates. Implications of results for model complexity in CFA are discussed. (SLD)
Descriptors: Estimation (Mathematics), Goodness of Fit, Higher Education, Mathematical Models
Peer reviewed Peer reviewed
Dumenci, Levent; Windle, Michael – Structural Equation Modeling, 1998
A generalization of the single trait, multioccasion measurement model is provided through a confirmatory measurement model for multitrait-multioccasion (MTMO) data. Several commonly used confirmatory measurement models are contrasted with the MTMO, and it is illustrated with a large four-wave dataset on family support and alcohol involvement. (SLD)
Descriptors: Alcohol Abuse, Item Response Theory, Mathematical Models, Multitrait Multimethod Techniques
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