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Raykov, Tenko; DiStefano, Christine; Calvocoressi, Lisa; Volker, Martin – Educational and Psychological Measurement, 2022
A class of effect size indices are discussed that evaluate the degree to which two nested confirmatory factor analysis models differ from each other in terms of fit to a set of observed variables. These descriptive effect measures can be used to quantify the impact of parameter restrictions imposed in an initially considered model and are free…
Descriptors: Effect Size, Models, Measurement Techniques, Factor Analysis
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Lee, Kejin; Whittaker, Tiffany Ann – AERA Online Paper Repository, 2017
The latent growth model (LGM) in structural equation modeling (SEM) may be extended to allow for the modeling of associations among multiple latent growth trajectories, resulting in a multiple domain latent growth model (MDLGM). While the MDLGM is conceived as a more powerful multivariate analysis technique, the examination of its methodological…
Descriptors: Statistical Analysis, Growth Models, Structural Equation Models, Multivariate Analysis
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Leckie, George; Prior, Lucy – School Effectiveness and School Improvement, 2022
School accountability systems increasingly hold schools to account for their performances using value-added models purporting to measure the effects of schools on student learning. The most common approach is to fit a linear regression of student current achievement on student prior achievement, where the school effects are the school means of the…
Descriptors: Value Added Models, Accountability, Secondary Schools, Educational Practices
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Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Journal of Educational and Behavioral Statistics, 2025
Analyzing heterogeneous treatment effects (HTEs) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and preintervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2024
Analyzing heterogeneous treatment effects (HTE) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and pre-intervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
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Duxbury, Scott W. – Sociological Methods & Research, 2023
This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…
Descriptors: Graphs, Scaling, Research Problems, Models
Moeyaert, Mariola – Behavioral Disorders, 2019
Multilevel meta-analysis is an innovative synthesis technique used for the quantitative integration of effect size estimates across participants and across studies. The quantitative summary allows for objective, evidence-based, and informed decisions in research, practice, and policy. Based on previous methodological work, the technique results in…
Descriptors: Meta Analysis, Evidence, Correlation, Predictor Variables
Kraft, Matthew A. – Annenberg Institute for School Reform at Brown University, 2019
Researchers commonly interpret effect sizes by applying benchmarks proposed by Cohen over a half century ago. However, effects that are small by Cohen's standards are large relative to the impacts of most field-based interventions. These benchmarks also fail to consider important differences in study features, program costs, and scalability. In…
Descriptors: Data Interpretation, Effect Size, Intervention, Benchmarking
Kim, Dong-In; Julian, Marc; Boughton, Keith; Phenow, Aurore – Online Submission, 2022
Pandemic-related policies are typically developed by districts and translated to all schools for implementation. Understanding the degree to which the pandemic impacted school-level performance would provide additional perspective for researchers looking to help district and school officials move forward. The main purpose of this study is to…
Descriptors: Pandemics, COVID-19, Academic Achievement, English
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Dunst, Carl J. – European Journal of Psychology and Educational Research, 2022
Findings from a research synthesis of the relationships between family needs and parent, family, and child functioning are reported. The synthesis included 31 studies conducted in 12 different countries. The studies were conducted between 1987 and 2021 and included 4,543 participants. Eight different family needs scales or adaptations of the…
Descriptors: Research Reports, Family Needs, Family Relationship, Outcome Measures
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Kelly, Sean; Ye, Feifei – Journal of Experimental Education, 2017
Educational analysts studying achievement and other educational outcomes frequently encounter an association between initial status and growth, which has important implications for the analysis of covariate effects, including group differences in growth. As explicated by Allison (1990), where only two time points of data are available, identifying…
Descriptors: Regression (Statistics), Models, Error of Measurement, Scores
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Koran, Jennifer – Measurement and Evaluation in Counseling and Development, 2016
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.
Descriptors: Factor Analysis, Sample Size, Models, Sampling
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Choi, Sunha – Health Education & Behavior, 2018
Using 2-year panel data, this study examined (1) whether experiencing financial hardship associated with out-of-pocket medical expenditures affected delaying/missing necessary health care in the following year; (2) whether such financial hardship mediated the effects of predisposing, enabling, and need characteristics on timely health care access…
Descriptors: Health Services, Health Behavior, Medical Care Evaluation, Medical Services
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Çogaltay, Nazim; Karadag, Engin – Educational Sciences: Theory and Practice, 2016
The purpose of this study is to test the effect of educational leadership on some organizational variables using meta-analysis method. In this context, the results of independent researches were merged together and the hypotheses created within the scope of the study were tested. In order to determine the researches to be included in the study,…
Descriptors: Foreign Countries, Instructional Leadership, Meta Analysis, Databases
Li, Dongmei; Yi, Qing; Harris, Deborah – ACT, Inc., 2017
In preparation for online administration of the ACT® test, ACT conducted studies to examine the comparability of scores between online and paper administrations, including a timing study in fall 2013, a mode comparability study in spring 2014, and a second mode comparability study in spring 2015. This report presents major findings from these…
Descriptors: College Entrance Examinations, Computer Assisted Testing, Comparative Analysis, Test Format
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