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Li, Wei; Konstantopoulos, Spyros – Educational and Psychological Measurement, 2023
Cluster randomized control trials often incorporate a longitudinal component where, for example, students are followed over time and student outcomes are measured repeatedly. Besides examining how intervention effects induce changes in outcomes, researchers are sometimes also interested in exploring whether intervention effects on outcomes are…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Longitudinal Studies, Hierarchical Linear Modeling
Moeyaert, Mariola; Yang, Panpan; Xu, Xinyun – Grantee Submission, 2021
This study investigated the power of two-level hierarchical linear modeling (HLM) to explain variability in intervention effectiveness between participants in context of single-case experimental design (SCED) research. HLM is a flexible technique that allows the inclusion of participant characteristics (e.g., age, gender, and disability types) as…
Descriptors: Hierarchical Linear Modeling, Intervention, Research Design, Participant Characteristics
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Xiao, ZhiMin; Higgins, Steve; Kasim, Adetayo – Journal of Experimental Education, 2019
Lord's Paradox occurs when a continuous covariate is statistically controlled for and the relationship between a continuous outcome and group status indicator changes in both magnitude and direction. This phenomenon poses a challenge to the notion of evidence-based policy, where data are supposed to be self-evident. We examined 50 effect size…
Descriptors: Statistical Analysis, Decision Making, Research Methodology, Scores
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Dong, Nianbo; Kelcey, Benjamin; Spybrook, Jessaca – Journal of Experimental Education, 2018
Researchers are often interested in whether the effects of an intervention differ conditional on individual- or group-moderator variables such as children's characteristics (e.g., gender), teacher's background (e.g., years of teaching), and school's characteristics (e.g., urbanity); that is, the researchers seek to examine for whom and under what…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Intervention, Effect Size
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Stallasch, Sophie E.; Lüdtke, Oliver; Artelt, Cordula; Brunner, Martin – Journal of Research on Educational Effectiveness, 2021
To plan cluster-randomized trials with sufficient statistical power to detect intervention effects on student achievement, researchers need multilevel design parameters, including measures of between-classroom and between-school differences and the amounts of variance explained by covariates at the student, classroom, and school level. Previous…
Descriptors: Foreign Countries, Randomized Controlled Trials, Intervention, Educational Research
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Rutherford, Marion; Forsyth, Kirsty; McKenzie, Karen; McClure, Iain; Murray, Aja; McCartney, Deborah; Irvine, Linda; O'Hare, Anne – Journal of Autism and Developmental Disorders, 2018
This study examined waiting times for diagnostic assessment of Autism Spectrum Disorder in 11 adult services, prior to and following the implementation of a 12 month change program. Methods to support change are reported and a multi-level modelling approach determined the effect of the change program on overall wait times. Results were…
Descriptors: Program Implementation, Models, Clinical Diagnosis, Autism
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Rhoads, Christopher – Journal of Educational and Behavioral Statistics, 2017
Researchers designing multisite and cluster randomized trials of educational interventions will usually conduct a power analysis in the planning stage of the study. To conduct the power analysis, researchers often use estimates of intracluster correlation coefficients and effect sizes derived from an analysis of survey data. When there is…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Surveys, Effect Size
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Talloen, Wouter; Moerkerke, Beatrijs; Loeys, Tom; De Naeghel, Jessie; Van Keer, Hilde; Vansteelandt, Stijn – Journal of Educational and Behavioral Statistics, 2016
To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within…
Descriptors: Intervention, Hierarchical Linear Modeling, Computation, Randomized Controlled Trials
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Sweet, Tracy M.; Junker, Brian W. – Journal of Educational and Behavioral Statistics, 2016
The hierarchical network model (HNM) is a framework introduced by Sweet, Thomas, and Junker for modeling interventions and other covariate effects on ensembles of social networks, such as what would be found in randomized controlled trials in education research. In this article, we develop calculations for the power to detect an intervention…
Descriptors: Intervention, Social Networks, Statistical Analysis, Computation
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Hembry, Ian; Bunuan, Rommel; Beretvas, S. Natasha; Ferron, John M.; Van den Noortgate, Wim – Journal of Experimental Education, 2015
A multilevel logistic model for estimating a nonlinear trajectory in a multiple-baseline design is introduced. The model is applied to data from a real multiple-baseline design study to demonstrate interpretation of relevant parameters. A simple change-in-levels (?"Levels") model and a model involving a quadratic function…
Descriptors: Computation, Research Design, Data, Intervention
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Smith, Daniel M.; Walls, Theodore A. – Measurement in Physical Education and Exercise Science, 2016
In sport and exercise research, examining both within- and between-individual variation is crucial. The ability to investigate change both within competitive events and across a competitive season is a priority for many sport researchers. The aim of this article is to demonstrate an approach to analyzing intensive longitudinal data collected…
Descriptors: Hierarchical Linear Modeling, Comparative Analysis, Athletics, Exercise
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Opitz, Elisabeth Moser; Grob, Urs; Wittich, Claudia; Häsel-Weide, Uta; Nührenbörger, Marcus – Learning Disabilities: A Contemporary Journal, 2018
Fostering peer interaction and shared learning is an important aim of inclusive instruction. However, it has not been established whether it is possible to offer explicit and intensive support for low achievers in inclusive settings. This longitudinal study examined whether a structured program that includes cooperative learning fosters…
Descriptors: Inclusion, Longitudinal Studies, Cooperative Learning, Competence
Buckley, Pamela; Moore, Brooke; Boardman, Alison G.; Arya, Diana J.; Maul, Andrew – American Educational Research Journal, 2017
K-12 intervention studies often include fidelity of implementation (FOI) as a mediating variable, though most do not report the validity of fidelity measures. This article discusses the critical need for validated FOI scales. To illustrate our point, we describe the development and validation of the Implementation Validity Checklist (IVC-R), an…
Descriptors: Intervention, Fidelity, Program Implementation, Test Validity
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Chen, Cheng-Chia; Seo, Dong-Chul; Lin, Hsien-Chang – Health Education Journal, 2018
Objective: The purpose of this longitudinal study was to examine the effects of state-level socioeconomic status (SES), the density of fast food restaurants and walking to work on body mass index (BMI) among US adults aged 50 years and older. The study sought further to account for the interaction effects of three different hierarchical levels of…
Descriptors: Longitudinal Studies, Older Adults, Body Composition, Socioeconomic Status
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Kruit, P. M.; Oostdam, R. J.; van den Berg, E.; Schuitema, J. A. – International Journal of Science Education, 2018
In most primary science classes, students are taught science inquiry skills by way of learning by doing. Research shows that explicit instruction may be more effective. The aim of this study was to investigate the effects of explicit instruction on the acquisition of inquiry skills. Participants included 705 Dutch fifth and sixth graders. Students…
Descriptors: Grade 5, Grade 6, Elementary School Science, Elementary School Students
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