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Tihomir Asparouhov; Bengt Muthén – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Penalized structural equation models (PSEM) is a new powerful estimation technique that can be used to tackle a variety of difficult structural estimation problems that can not be handled with previously developed methods. In this paper we describe the PSEM framework and illustrate the quality of the method with simulation studies.…
Descriptors: Structural Equation Models, Computation, Factor Analysis, Measurement Techniques
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Kjorte Harra; David Kaplan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…
Descriptors: Structural Equation Models, Bayesian Statistics, Regression (Statistics), Statistical Inference
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Daniel Seddig – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The latent growth model (LGM) is a popular tool in the social and behavioral sciences to study development processes of continuous and discrete outcome variables. A special case are frequency measurements of behaviors or events, such as doctor visits per month or crimes committed per year. Probability distributions for such outcomes include the…
Descriptors: Growth Models, Statistical Analysis, Structural Equation Models, Crime
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Gonzales, Joseph E. – Measurement: Interdisciplinary Research and Perspectives, 2021
JMP® Pro has introduced a new structural equation modeling (SEM) platform to its suite of multivariate methods of analysis. Utilizing their graphical user interface, JMP Pro has created a SEM platform that is easily navigable for both experienced and novice SEM users. As a new platform, JMP Pro does not have the capacity to implement certain…
Descriptors: Structural Equation Models, Multivariate Analysis, Usability, Factor Analysis
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Rohit Batra; Silvia A. Bunge; Emilio Ferrer – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Studying development processes, as they unfold over time, involves collecting repeated measures from individuals and modeling the changes over time. One methodological challenge in this type of longitudinal data is separating retest effects, due to the repeated assessments, from developmental processes such as maturation or age. In this article,…
Descriptors: Children, Adolescents, Longitudinal Studies, Test Reliability
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Serang, Sarfaraz – New Directions for Child and Adolescent Development, 2021
Longitudinal research is often interested in identifying correlates of heterogeneity in change. This paper compares three approaches for doing so: the mixed-effects model (latent growth curve model), the growth mixture model, and structural equation model trees. Each method is described, with special focus given to how each structures…
Descriptors: Longitudinal Studies, National Surveys, Growth Models, Structural Equation Models
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Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2019
Longitudinal data analysis has received widespread interest throughout educational, behavioral, and social science research, with latent growth curve modeling currently being one of the most popular methods of analysis. Despite the popularity of latent growth curve modeling, limited attention has been directed toward understanding the issues of…
Descriptors: Reliability, Longitudinal Studies, Growth Models, Structural Equation Models
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McNeish, Daniel – Journal of Experimental Education, 2018
Small samples are common in growth models due to financial and logistical difficulties of following people longitudinally. For similar reasons, longitudinal studies often contain missing data. Though full information maximum likelihood (FIML) is popular to accommodate missing data, the limited number of studies in this area have found that FIML…
Descriptors: Growth Models, Sampling, Sample Size, Hierarchical Linear Modeling
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Kim, Minjung; Kwok, Oi-Man; Yoon, Myeongsun; Willson, Victor; Lai, Mark H. C. – Journal of Experimental Education, 2016
This study investigated the optimal strategy for model specification search under the latent growth modeling (LGM) framework, specifically on searching for the correct polynomial mean or average growth model when there is no a priori hypothesized model in the absence of theory. In this simulation study, the effectiveness of different starting…
Descriptors: Statistical Analysis, Growth Models, Simulation, Structural Equation Models
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Dennie, David; Acharya, Parul; Greer, Deirdre; Bryant, Camille – Psychology in the Schools, 2019
The study examined the extent that teacher-student relationships (TSR) influenced basic psychological needs, engagement, and student growth using the self-systems process model as a framework using structural equation modeling. Based on prior research, it was hypothesized that context (TSR) influenced self (basic psychological needs), which…
Descriptors: Teacher Student Relationship, Class Activities, Learner Engagement, Grade 7
Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Elliott, Stephen N. – Journal of Special Education, 2017
Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state's mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four…
Descriptors: Classification, Achievement Gains, Special Needs Students, Mathematics Achievement
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von Davier, Alina A.; Carstensen, Claus H.; von Davier, Matthias – ETS Research Report Series, 2006
Measuring and linking competencies require special instruments, special data collection designs, and special statistical models. The measurement instruments are tests or tests forms, which can be used in the following situations: The same test can be given repeatedly; two or more parallel tests forms (i.e., forms intended to be similar in…
Descriptors: Scores, Measurement Techniques, Competence, Comparative Analysis