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Xijuan Zhang; Hao Wu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A full structural equation model (SEM) typically consists of both a measurement model (describing relationships between latent variables and observed scale items) and a structural model (describing relationships among latent variables). However, often researchers are primarily interested in testing hypotheses related to the structural model while…
Descriptors: Structural Equation Models, Goodness of Fit, Robustness (Statistics), Factor Structure
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Mikkel Helding Vembye; James Eric Pustejovsky; Therese Deocampo Pigott – Research Synthesis Methods, 2024
Sample size and statistical power are important factors to consider when planning a research synthesis. Power analysis methods have been developed for fixed effect or random effects models, but until recently these methods were limited to simple data structures with a single, independent effect per study. Recent work has provided power…
Descriptors: Sample Size, Robustness (Statistics), Effect Size, Social Science Research
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Anders Holm; Anders Hjorth-Trolle; Robert Andersen – Sociological Methods & Research, 2025
Lagged dependent variables (LDVs) are often used as predictors in ordinary least squares (OLS) models in the social sciences. Although several estimators are commonly employed, little is known about their relative merits in the presence of classical measurement error and different longitudinal processes. We assess the performance of four commonly…
Descriptors: Elementary Education, Scores, Error of Measurement, Predictor Variables
Luke W. Miratrix; Jasjeet S. Sekhon; Alexander G. Theodoridis; Luis F. Campos – Grantee Submission, 2018
The popularity of online surveys has increased the prominence of using weights that capture units' probabilities of inclusion for claims of representativeness. Yet, much uncertainty remains regarding how these weights should be employed in analysis of survey experiments: Should they be used or ignored? If they are used, which estimators are…
Descriptors: Online Surveys, Weighted Scores, Data Interpretation, Robustness (Statistics)
Goldhaber, Dan; Chaplin, Duncan – Center for Education Data & Research, 2012
In a provocative and influential paper, Jesse Rothstein (2010) finds that standard value added models (VAMs) suggest implausible future teacher effects on past student achievement, a finding that obviously cannot be viewed as causal. This is the basis of a falsification test (the Rothstein falsification test) that appears to indicate bias in VAM…
Descriptors: School Effectiveness, Teacher Effectiveness, Achievement Gains, Statistical Bias
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Lincove, Jane Arnold; Osborne, Cynthia; Dillon, Amanda; Mills, Nicholas – Journal of Teacher Education, 2014
Despite questions about validity and reliability, the use of value-added estimation methods has moved beyond academic research into state accountability systems for teachers, schools, and teacher preparation programs (TPPs). Prior studies of value-added measurement for TPPs test the validity of researcher-designed models and find that measuring…
Descriptors: Teacher Education Programs, Accountability, Politics of Education, School Statistics
Grays, Makayla – ProQuest LLC, 2013
Students must be sufficiently motivated in order to achieve the intended learning outcomes of their college courses. Research in education and psychology has found motivation to be context-dependent. Therefore, students' motivation is likely to differ from one semester to the next according to which courses students are taking. However, there are…
Descriptors: Longitudinal Studies, Student Motivation, Predictor Variables, Psychometrics
Ballou, Dale – National Education Policy Center, 2012
A new report titled "The Long-Term Impacts of Teachers" concludes that teachers whose students tend to show high gains on their test scores (called "high value-added teachers") also contribute to later student success in young adulthood, as indicated by outcomes such as college attendance and future earnings. To support this claim, it is not…
Descriptors: Evidence, Achievement Gains, High Achievement, Teacher Effectiveness