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Lanza, Stephanie T.; Tan, Xianming; Bray, Bethany C. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Although prediction of class membership from observed variables in latent class analysis is well understood, predicting an observed distal outcome from latent class membership is more complicated. A flexible model-based approach is proposed to empirically derive and summarize the class-dependent density functions of distal outcomes with…
Descriptors: Structural Equation Models, Monte Carlo Methods, Comparative Analysis, Statistical Analysis
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Peugh, James L.; DiLillo, David; Panuzio, Jillian – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Mixed-dyadic data, collected from distinguishable (nonexchangeable) or indistinguishable (exchangeable) dyads, require statistical analysis techniques that model the variation within dyads and between dyads appropriately. The purpose of this article is to provide a tutorial for performing structural equation modeling analyses of cross-sectional…
Descriptors: Structural Equation Models, Data Analysis, Statistical Analysis, Computer Software
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Ferrando, Pere J.; Anguiano-Carrasco, Cristina; Demestre, Josep – Structural Equation Modeling: A Multidisciplinary Journal, 2013
This article proposes a model-based procedure, intended for personality measures, for exploiting the auxiliary information provided by the certainty with which individuals answer every item (response certainty). This information is used to (a) obtain more accurate estimates of individual trait levels, and (b) provide a more detailed assessment of…
Descriptors: Structural Equation Models, Item Response Theory, Personality Measures, Goodness of Fit
Leung, Man-Tak; Lee, Wing-Shan – Australian Association for Research in Education, 2013
Present study, was conducted to explore the impact of parenting on self-regulated learning with mediating effect for learning motivation. The sample of the study consisted of 210 students which was conveniently sampled from universities in Hong Kong. Designed Questionnaire was used to collect the data. Confirmatory factor analysis was conducted to…
Descriptors: Foreign Countries, Parenting Styles, Learning Motivation, Independent Study
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Burt, Keith B.; Obradovic, Jelena – Developmental Review, 2013
The purpose of this paper is to review major statistical and psychometric issues impacting the study of psychophysiological reactivity and discuss their implications for applied developmental researchers. We first cover traditional approaches such as the observed difference score (DS) and the observed residual score (RS), including a review of…
Descriptors: Measurement Techniques, Psychometrics, Data Analysis, Researchers
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Kline, Rex B. – Educational Research and Evaluation, 2013
Test fairness and test bias are not synonymous concepts. Test bias refers to statistical evidence that the psychometrics or interpretation of test scores depend on group membership, such as gender or race, when such differences are not expected. A test that is grossly biased may be judged to be unfair, but test fairness concerns the broader, more…
Descriptors: Factor Analysis, Social Justice, Psychometrics, Test Bias
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Wainer, Howard – Journal of Educational and Behavioral Statistics, 2011
This article presents an interview with Karl Gustav Joreskog. Karl Gustav Joreskog was born in Amal, Sweden, on April 25, 1935. He did his undergraduate studies at Uppsala University from 1955 to 1957, with a major in mathematics and physics. He received a PhD in statistics at Uppsala University in 1963, and he was a research statistician at…
Descriptors: Statistics, Structural Equation Models, Computer Software, Factor Analysis
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Menard, Scott – Social Forces, 2011
Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…
Descriptors: Regression (Statistics), Standards, Computation, Structural Equation Models
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Tueller, Stephen J.; Drotar, Scott; Lubke, Gitta H. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
The discrimination between alternative models and the detection of latent classes in the context of latent variable mixture modeling depends on sample size, class separation, and other aspects that are related to power. Prior to a mixture analysis it is useful to investigate model performance in a simulation study that reflects the research…
Descriptors: Simulation, Structural Equation Models, Statistical Analysis, Mathematics
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Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…
Descriptors: Structural Equation Models, Bayesian Statistics, Comparative Analysis, Computation
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Heene, Moritz; Hilbert, Sven; Draxler, Clemens; Ziegler, Matthias; Buhner, Markus – Psychological Methods, 2011
Fit indices are widely used in order to test the model fit for structural equation models. In a highly influential study, Hu and Bentler (1999) showed that certain cutoff values for these indices could be derived, which, over time, has led to the reification of these suggested thresholds as "golden rules" for establishing the fit or other aspects…
Descriptors: Goodness of Fit, Factor Analysis, Structural Equation Models, Statistical Analysis
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Sterba, Sonya K. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article relates a still-popular motivation for using parceling to an unrecognized cost. The still-popular motivation is improvement in fit with respect to the item-solution. The cost is uncertainty in fit due to the selection of one out of many possible item-to-parcel allocations. A theoretical framework establishes the reason for this…
Descriptors: Goodness of Fit, Factor Analysis, Structural Equation Models, Statistical Analysis
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Ledermann, Thomas; Macho, Siegfried; Kenny, David A. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
The assessment of mediation in dyadic data is an important issue if researchers are to test process models. Using an extended version of the actor-partner interdependence model the estimation and testing of mediation is complex, especially when dyad members are distinguishable (e.g., heterosexual couples). We show how the complexity of the model…
Descriptors: Structural Equation Models, Sampling, Statistical Inference, Interpersonal Relationship
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Song, Xin-Yuan; Lu, Zhao-Hua; Hser, Yih-Ing; Lee, Sik-Yum – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article considers a Bayesian approach for analyzing a longitudinal 2-level nonlinear structural equation model with covariates, and mixed continuous and ordered categorical variables. The first-level model is formulated for measures taken at each time point nested within individuals for investigating their characteristics that are dynamically…
Descriptors: Structural Equation Models, Longitudinal Studies, Bayesian Statistics, Drug Use
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de la Torre, Jimmy – Psychometrika, 2011
The G-DINA ("generalized deterministic inputs, noisy and gate") model is a generalization of the DINA model with more relaxed assumptions. In its saturated form, the G-DINA model is equivalent to other general models for cognitive diagnosis based on alternative link functions. When appropriate constraints are applied, several commonly used…
Descriptors: Structural Equation Models, Identification, Models, Comparative Analysis
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