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Jie Fang; Zhonglin Wen; Kit-Tai Hau – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e.,…
Descriptors: Structural Equation Models, Mediation Theory, Data Analysis, Longitudinal Studies
Allison R. Lombardi; Graham G. Rifenbark; Ashley Taconet – Exceptional Children, 2023
Secondary data analyses occur when new analyses are proposed for existing data. Although they are prevalent in special education research, there is little guidance on how to prepare secondary data analyses studies. Preregistration of secondary data analyses studies provides a nice opportunity and structure for fellow researchers to share…
Descriptors: Data Analysis, Special Education, Educational Research, Longitudinal Studies
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Quimby, Barbara; Beresford, Melissa – Field Methods, 2023
Participatory modeling (PM) is an engaged research methodology for creating analog or computer-based models of complex systems, such as socio-environmental systems. Used across a range of fields, PM centers stakeholder knowledge and participation to create more internally valid models that can inform policy and increase engagement and trust…
Descriptors: Research Methodology, Models, Stakeholders, World Views
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Goldhaber, Dan; Theobald, Roddy – Educational Evaluation and Policy Analysis, 2023
We contextualize the magnitude of teacher attrition during the pandemic, including from the 2020-2021 school year to the 2021-2022 school year, using longitudinal data on teachers in Washington since the 1984-1985 school year. The teacher attrition rate after the 2020-2021 school year (7.3%) increased by almost one percentage point from the…
Descriptors: Faculty Mobility, COVID-19, Pandemics, Longitudinal Studies
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Hecht, Martin; Voelkle, Manuel C. – International Journal of Behavioral Development, 2021
The analysis of cross-lagged relationships is a popular approach in prevention research to explore the dynamics between constructs over time. However, a limitation of commonly used cross-lagged models is the requirement of equally spaced measurement occasions that prevents the usage of flexible longitudinal designs and complicates cross-study…
Descriptors: Models, Longitudinal Studies, Prevention, Time
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Wu, Wei; Jia, Fan – New Directions for Child and Adolescent Development, 2021
Longitudinal panel studies are widely used in developmental science to address important research questions on human development across the lifespan. These studies, however, are often challenging to implement. They can be costly, time-consuming, and vulnerable to test--retest effects or high attrition over time. Planned missingness designs (PMDs),…
Descriptors: Longitudinal Studies, Research Design, Data Analysis, Developmental Psychology
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von Hippel, Paul T. – Sociological Methods & Research, 2020
When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…
Descriptors: Computation, Error of Measurement, Data Analysis, Children
Tennessee Higher Education Commission, 2024
The 2024 Articulation and Transfer Report provides an update on the progress made toward full articulation between public institutions in Tennessee. This report uses data from National Student Clearinghouse Student Tracker (NSC), the Tennessee Higher Education Commission's Student Information System (THECSIS), and the Tennessee Board of Regents…
Descriptors: Articulation (Education), Higher Education, Data Analysis, Transfer Rates (College)
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Amaliah, Dewi; Cook, Dianne; Tanaka, Emi; Hyde, Kate; Tierney, Nicholas – Journal of Statistics and Data Science Education, 2022
Textbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection. It is also important to use contemporary data for teaching, to imbue the sense…
Descriptors: Statistics Education, Data Science, Textbooks, Data Analysis
Zhang, Zhiyong; Liu, Haiyan – Grantee Submission, 2018
Latent change score models (LCSMs) proposed by McArdle (McArdle, 2000, 2009; McArdle & Nesselroade, 1994) offer a powerful tool for longitudinal data analysis. They are becoming increasingly popular in social and behavioral research (e.g., Gerstorf et al., 2007; Ghisletta & Lindenberger, 2005; King et al., 2006; Raz et al., 2008). Although…
Descriptors: Sample Size, Monte Carlo Methods, Data Analysis, Models
Education Trust-West, 2019
With Governor Newsom's signature on the state budget in June 2019, California is finally on the path to joining the majority of other states in the country who have robust data systems. Having this administration provide funding to begin to build and maintain a statewide longitudinal data system (SLDS) is an important win. Advocates have been…
Descriptors: Longitudinal Studies, Data Collection, Equal Education, Family Involvement
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Harring, Jeffrey R.; Johnson, Tessa L. – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module…
Descriptors: Educational Assessment, Data Analysis, Longitudinal Studies, Case Studies
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Gilman, Rich; Carboni, Inga; Perry, Andrew; Anderman, Eric M. – School Psychology, 2022
Social network analysis (SNA) consists of a broad set of frameworks and methods to assess how direct and indirect relationships influence individual functioning. Although interest in SNA has steadily increased in the psychological sciences, school psychology has not kept pace. This article provides a general overview of core SNA concepts,…
Descriptors: Social Networks, Network Analysis, School Psychology, Data Analysis
Data Quality Campaign, 2021
The 2020 election brought about legislative change across the country. New and veteran policymakers need information about the schools in their state. What programs are the most cost effective and work best for students? How can states attract and retain great teachers? What information do parents need to ensure that their kids are on track to…
Descriptors: Educational Policy, Policy Formation, Data Collection, Data Analysis
McKay, Heather; Haviland, Sara; Michael, Suzanne – Western Interstate Commission for Higher Education, 2020
The Multistate Longitudinal Data Exchange (MLDE) facilitates data sharing between states from K-12 education, higher education, and labor agencies. Its goal is to provide practitioners, policymakers, and researchers with a comprehensive data source to understand educational and career trajectories, including how these trajectories can cross state…
Descriptors: Trust (Psychology), Longitudinal Studies, State Universities, State Agencies
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