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Showing all 10 results Save | Export
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Dae Woong Ham; Luke Miratrix – Grantee Submission, 2024
The consequence of a change in school leadership (e.g., principal turnover) on student achievement has important implications for education policy. The impact of such an event can be estimated via the popular Difference in Difference (DiD) estimator, where those schools with a turnover event are compared to a selected set of schools that did not…
Descriptors: Trend Analysis, Faculty Mobility, Academic Achievement, Principals
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Emma Somer; Carl Falk; Milica Miocevic – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…
Descriptors: Scores, Structural Equation Models, Comparative Analysis, Sample Size
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Son, Sookyoung; Lee, Hyunjung; Jang, Yoona; Yang, Junyeong; Hong, Sehee – Educational and Psychological Measurement, 2019
The purpose of the present study is to compare nonnormal distributions (i.e., t, skew-normal, skew-t with equal skew and skew-t with unequal skew) in growth mixture models (GMMs) based on diverse conditions of a number of time points, sample sizes, and skewness for intercepts. To carry out this research, two simulation studies were conducted with…
Descriptors: Statistical Distributions, Statistical Analysis, Structural Equation Models, Comparative Analysis
Mai, Yujiao; Zhang, Zhiyong; Wen, Zhonglin – Grantee Submission, 2018
Exploratory structural equation modeling (ESEM) is an approach for analysis of latent variables using exploratory factor analysis to evaluate the measurement model. This study compared ESEM with two dominant approaches for multiple regression with latent variables, structural equation modeling (SEM) and manifest regression analysis (MRA). Main…
Descriptors: Structural Equation Models, Multiple Regression Analysis, Comparative Analysis, Statistical Bias
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Savalei, Victoria; Rhemtulla, Mijke – Journal of Educational and Behavioral Statistics, 2017
In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately…
Descriptors: Computation, Statistical Analysis, Test Items, Maximum Likelihood Statistics
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Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C. – Educational and Psychological Measurement, 2018
Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…
Descriptors: Error of Measurement, Testing, Scores, Models
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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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Geiser, Christian; Eid, Michael; West, Stephen G.; Lischetzke, Tanja; Nussbeck, Fridtjof W. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Multimethod data analysis is a complex procedure that is often used to examine the degree to which different measures of the same construct converge in the assessment of this construct. Several authors have called for a greater understanding of the definition and meaning of method effects in different models for multimethod data. In this article,…
Descriptors: Structural Equation Models, Factor Analysis, Multitrait Multimethod Techniques, Comparative Analysis
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DeMars, Christine E. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
In structural equation modeling software, either limited-information (bivariate proportions) or full-information item parameter estimation routines could be used for the 2-parameter item response theory (IRT) model. Limited-information methods assume the continuous variable underlying an item response is normally distributed. For skewed and…
Descriptors: Item Response Theory, Structural Equation Models, Computation, Computer Software
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Byrne, Barbara M.; van de Vijver, Fons J. R. – International Journal of Testing, 2010
A critical assumption in cross-cultural comparative research is that the instrument measures the same construct(s) in exactly the same way across all groups (i.e., the instrument is measurement and structurally equivalent). Structural equation modeling (SEM) procedures are commonly used in testing these assumptions of multigroup equivalence.…
Descriptors: Measures (Individuals), Cross Cultural Studies, Measurement, Comparative Analysis