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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
Brendan A. Schuetze – Educational Psychology Review, 2024
The computational model of school achievement represents a novel approach to theorizing school achievement, conceptualizing educational interventions as modifications to students' learning curves. By modeling the process and products of educational achievement simultaneously, this tool addresses several unresolved questions in educational…
Descriptors: Computation, Growth Models, Academic Achievement, Student Evaluation
Richa Ghevarghese – ProQuest LLC, 2022
Growth mixture modeling (GMM) is a methodological tool used to represent heterogeneity in longitudinal datasets through the identification of unobserved subgroups following qualitatively and quantitatively distinct trajectories in a population. These growth trajectories or functional forms are informed by the underlying developmental theory, are…
Descriptors: Monte Carlo Methods, Longitudinal Studies, Simulation, Growth Models
Fay, Derek M.; Levy, Roy; Schulte, Ann C. – Journal of Experimental Education, 2022
Longitudinal data structures are frequently encountered in a variety of disciplines in the social and behavioral sciences. Growth curve modeling offers a highly extensible framework that allows for the exploration of rich hypotheses. However, owing to the presence of interrelated sources of potential data-model misfit at multiple levels, the…
Descriptors: Measurement, Models, Bayesian Statistics, Hierarchical Linear Modeling
Dong, Yixiao; Dumas, Denis; Clements, Douglas H.; Sarama, Julie – Journal of Experimental Education, 2023
Dynamic Measurement Modeling (DMM) is a recently-developed measurement framework for gauging developing constructs (e.g., learning capacity) that conventional single-timepoint tests cannot assess. The current project developed a person-specific DMM Trajectory Deviance Index (TDI) that captures the aberrance of an individual's growth from the…
Descriptors: Measurement Techniques, Simulation, Student Development, Educational Research
Fan Pan – ProQuest LLC, 2021
This dissertation informed researchers about the performance of different level-specific and target-specific model fit indices in Multilevel Latent Growth Model (MLGM) using unbalanced design and different trajectories. As the use of MLGMs is a relatively new field, this study helped further the field by informing researchers interested in using…
Descriptors: Goodness of Fit, Item Response Theory, Growth Models, Monte Carlo Methods
Samonte, Kelli Marie – ProQuest LLC, 2017
Longitudinal data analysis assumes that scales meet the assumption of longitudinal measurement invariance (i.e., that scales function equivalently across measurement occasions). This simulation study examines the impact of violations to the assumption of longitudinal measurement invariance on growth models and whether modeling the invariance…
Descriptors: Test Bias, Growth Models, Longitudinal Studies, Simulation
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
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
Monroe, Scott; Cai, Li – Educational Measurement: Issues and Practice, 2015
Student growth percentiles (SGPs, Betebenner, 2009) are used to locate a student's current score in a conditional distribution based on the student's past scores. Currently, following Betebenner (2009), quantile regression (QR) is most often used operationally to estimate the SGPs. Alternatively, multidimensional item response theory (MIRT) may…
Descriptors: Item Response Theory, Reliability, Growth Models, Computation
Monroe, Scott; Cai, Li – Grantee Submission, 2015
Student Growth Percentiles (SGP, Betebenner, 2009) are used to locate a student's current score in a conditional distribution based on the student's past scores. Currently, following Betebenner (2009), quantile regression is most often used operationally to estimate the SGPs. Alternatively, multidimensional item response theory (MIRT) may also be…
Descriptors: Item Response Theory, Reliability, Growth Models, Computation
McNeish, Daniel; Harring, Jeffrey R. – Educational and Psychological Measurement, 2017
To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data-model fit. However, previous studies have demonstrated poor…
Descriptors: Growth Models, Goodness of Fit, Error Correction, Sampling