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Liu, Jin; Perera, Robert A.; Kang, Le; Sabo, Roy T.; Kirkpatrick, Robert M. – Journal of Educational and Behavioral Statistics, 2022
This study proposes transformation functions and matrices between coefficients in the original and reparameterized parameter spaces for an existing linear-linear piecewise model to derive the interpretable coefficients directly related to the underlying change pattern. Additionally, the study extends the existing model to allow individual…
Descriptors: Longitudinal Studies, Statistical Analysis, Matrices, Mathematics
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
Tomek, Sara; Robinson, Cecil – Measurement: Interdisciplinary Research and Perspectives, 2021
Typical longitudinal growth models assume constant functional growth over time. However, there are often conditions where trajectories may not be constant over time. For example, trajectories of psychological behaviors may vary based on a participant's age, or conversely, participants may experience an intervention that causes trajectories to…
Descriptors: Growth Models, Statistical Analysis, Hierarchical Linear Modeling, Computation
Nazari, Sanaz; Leite, Walter L.; Huggins-Manley, A. Corinne – Journal of Experimental Education, 2023
The piecewise latent growth models (PWLGMs) can be used to study changes in the growth trajectory of an outcome due to an event or condition, such as exposure to an intervention. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM. A comparison of these models is…
Descriptors: Growth Models, Statistical Analysis, Intervention, Comparative Analysis
Li, Wei; Konstantopoulos, Spyros – Journal of Experimental Education, 2019
Education experiments frequently assign students to treatment or control conditions within schools. Longitudinal components added in these studies (e.g., students followed over time) allow researchers to assess treatment effects in average rates of change (e.g., linear or quadratic). We provide methods for a priori power analysis in three-level…
Descriptors: Research Design, Statistical Analysis, Sample Size, Effect Size
Soland, James; Thum, Yeow Meng – Journal of Research on Educational Effectiveness, 2022
Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…
Descriptors: Academic Achievement, Longitudinal Studies, Data Use, Computation
Pivovarova, Margarita; Amrein-Beardsley, Audrey – Educational Assessment, 2018
While states are no longer required to set up teacher evaluation systems based in significant part on student test scores, quite a few continue to use value-added (VAMs) or student growth percentile (SGP) models for that purpose. In this study, we analyzed three years of teacher data to illustrate the performance of teachers' median growth…
Descriptors: Growth Models, Teacher Evaluation, Value Added Models, Reliability
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
Guerra-Peña, Kiero; Steinley, Douglas – Educational and Psychological Measurement, 2016
Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…
Descriptors: Growth Models, Bayesian Statistics, Sampling, Statistical Inference
Clemens, Nathan H.; Lai, Mark H. C.; Burke, Mack; Wu, Jiun-Yu – School Psychology Review, 2017
Although letter naming fluency (LNF) and letter sound fluency (LSF) measures are widely available to educators for assessing early literacy skills of kindergarten children, better understanding of the contributions of these skills to reading development can help improve the interpretation of LNF and LSF data for instructional decisions. This study…
Descriptors: Alphabets, Naming, Reading Fluency, Emergent Literacy
Wrabel, Stephani L.; Saultz, Andrew; Polikoff, Morgan S.; McEachin, Andrew; Duque, Matthew – Educational Policy, 2018
Executive leadership of the U.S. Department of Education (USDOE) initiated a flexibility offering from No Child Left Behind. Our work explores specific design decisions made in these state-specific accountability systems as associated with state political environments, resources, and demographic characteristics. Our analysis, focused on 42 states…
Descriptors: Elementary Secondary Education, Politics of Education, Educational Legislation, Federal Legislation
Zettler-Greeley, Cynthia M.; Bailet, Laura L.; Murphy, Suzanne; DeLucca, Teri; Branum-Martin, Lee – Early Education and Development, 2018
Research Findings: This study reports outcomes from a randomized, controlled trial of an emergent literacy intervention for prekindergarten children at-risk for reading failure. Children (N = 2219) in 114 preschools and childcare centers were screened for eligibility in fall. Children who scored at-risk (n = 476) were randomized to fall or spring…
Descriptors: Program Effectiveness, Emergent Literacy, Literacy Education, Intervention
Ober, David R.; Beekman, John A.; Pierce, Rebecca L. – Journal of Education and Training Studies, 2018
This paper examines the graduation rates between 2000 and 2015 of United States colleges and universities at the national, state, and institutional levels. This research focuses on two-year and four-year programs. Rates are investigated longitudinally along with variables that distinguish between public/private institutions, percentages of…
Descriptors: Graduation Rate, Longitudinal Studies, Growth Models, Part Time Students
Kruk, Richard S.; Luther Ruban, Cassia – Journal of Learning Disabilities, 2018
Visual processes in Grade 1 were examined for their predictive influences in nonalphanumeric and alphanumeric rapid naming (RAN) in 51 poor early and 69 typical readers. In a lagged design, children were followed longitudinally from Grade 1 to Grade 3 over 5 testing occasions. RAN outcomes in early Grade 2 were predicted by speeded and nonspeeded…
Descriptors: Naming, Reading Difficulties, Grade 1, Grade 2
Xu, Xianxuan; Grant, Leslie W.; Ward, Thomas J. – NASSP Bulletin, 2016
This study examines the validity of a statewide teacher evaluation system in the Commonwealth of Virginia. Three hundred and thirty-eight teachers from 16 at-risk schools located in eight school districts participated in an evaluation system pilot during the 2011-2012 academic year. Teachers received ratings on six teacher effectiveness process…
Descriptors: Teacher Evaluation, Validity, State Programs, Scores
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