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Lane, Sean P.; Kelleher, Bridgette L. – Developmental Psychology, 2023
Recruiting participants for studies of early-life longitudinal development is challenging, often resulting in practical upper bounds in sample size and missing data due to attrition. These factors pose risks for the statistical power of such studies depending on the intended analytic model. One mitigation strategy is to increase measurement…
Descriptors: Longitudinal Studies, Child Development, Hierarchical Linear Modeling, Research Design
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Mariola Moeyaert; Panpan Yang; Yukang Xue – Journal of Experimental Education, 2024
We have entered an era in which scientific evidence increasingly informs research practice and policy. As there is an exponential increase in the use of single-case experimental designs (SCEDs) to evaluate intervention effectiveness, there is accumulating evidence available for quantitative synthesis. Consequently, there is a growing interest in…
Descriptors: Meta Analysis, Research Design, Synthesis, Patients
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Raykov, Tenko; Menold, Natalja; Leer, Jane – Educational and Psychological Measurement, 2022
Two- and three-level designs in educational and psychological research can involve entire populations of Level-3 and possibly Level-2 units, such as schools and educational districts nested within a given state, or neighborhoods and counties in a state. Such a design is of increasing relevance in empirical research owing to the growing popularity…
Descriptors: Hierarchical Linear Modeling, Computation, Statistical Analysis, Research Design
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Timothy Lycurgus; Daniel Almirall – Society for Research on Educational Effectiveness, 2024
Background: Education scientists are increasingly interested in constructing interventions that are adaptive over time to suit the evolving needs of students, classrooms, or schools. Such "adaptive interventions" (also referred to as dynamic treatment regimens or dynamic instructional regimes) determine which treatment should be offered…
Descriptors: Educational Research, Research Design, Randomized Controlled Trials, Intervention
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Wei Li; Yanli Xie; Dung Pham; Nianbo Dong; Jessaca Spybrook; Benjamin Kelcey – Asia Pacific Education Review, 2024
Cluster randomized trials (CRTs) are commonly used to evaluate the causal effects of educational interventions, where the entire clusters (e.g., schools) are randomly assigned to treatment or control conditions. This study introduces statistical methods for designing and analyzing two-level (e.g., students nested within schools) and three-level…
Descriptors: Research Design, Multivariate Analysis, Randomized Controlled Trials, Hierarchical Linear Modeling
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Raykov, Tenko; DiStefano, Christine – Educational and Psychological Measurement, 2022
A latent variable modeling-based procedure is discussed that permits to readily point and interval estimate the design effect index in multilevel settings using widely circulated software. The method provides useful information about the relationship of important parameter standard errors when accounting for clustering effects relative to…
Descriptors: Hierarchical Linear Modeling, Correlation, Evaluation, Research Design
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Kyle Cox; Ben Kelcey; Hannah Luce – Journal of Experimental Education, 2024
Comprehensive evaluation of treatment effects is aided by considerations for moderated effects. In educational research, the combination of natural hierarchical structures and prevalence of group-administered or shared facilitator treatments often produces three-level partially nested data structures. Literature details planning strategies for a…
Descriptors: Randomized Controlled Trials, Monte Carlo Methods, Hierarchical Linear Modeling, Educational Research
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Shen, Zuchao; Kelcey, Benjamin – Journal of Research on Educational Effectiveness, 2022
Optimal sampling frameworks attempt to identify the most efficient sampling plans to achieve an adequate statistical power. Although such calculations are theoretical in nature, they are critical to the judicious and wise use of funding because they serve as important starting points that guide practical discussions around sampling tradeoffs and…
Descriptors: Sampling, Research Design, Randomized Controlled Trials, Statistical Analysis
Olasunkanmi James Kehinde – ProQuest LLC, 2024
The Q-matrix played a key role in implementations of diagnostic classification models (DCMs) or cognitive diagnostic models (CDMs) -- a family of psychometric models that are gaining attention in providing diagnostic information on students' mastery of cognitive attributes or skills. Using two Monte Carlo simulation studies, this dissertation…
Descriptors: Diagnostic Tests, Q Methodology, Learning Trajectories, Sample Size
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Paul Thompson; Kaydee Owen; Richard P. Hastings – International Journal of Research & Method in Education, 2024
Traditionally, cluster randomized controlled trials are analyzed with the average intervention effect of interest. However, in populations that contain higher degrees of heterogeneity or variation may differ across different values of a covariate, which may not be optimal. Within education and social science contexts, exploring the variation in…
Descriptors: Randomized Controlled Trials, Intervention, Mathematics Education, Mathematics Skills
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Fangxing Bai; Benjamin Kelcey; Yanli Xie; Kyle Cox – Society for Research on Educational Effectiveness, 2022
Background: Regression Discontinuous Design (RDD) is widely used in educational studies. Through RDD, researchers can obtain unbiased results when Randomized Experimental Design (RED) is inaccessible. Compared to RED, the RDD only requires a cut score variable (continuous) and a cutoff value to assign students to the treatment or control groups.…
Descriptors: Research Design, Regression (Statistics), Hierarchical Linear Modeling, Mediation Theory
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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
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Li, Wei; Dong, Nianbo; Maynarad, Rebecca; Spybrook, Jessaca; Kelcey, Ben – Journal of Research on Educational Effectiveness, 2023
Cluster randomized trials (CRTs) are commonly used to evaluate educational interventions, particularly their effectiveness. Recently there has been greater emphasis on using these trials to explore cost-effectiveness. However, methods for establishing the power of cluster randomized cost-effectiveness trials (CRCETs) are limited. This study…
Descriptors: Research Design, Statistical Analysis, Randomized Controlled Trials, Cost Effectiveness
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Shirilla, Paul; Solid, Craig; Graham, Suzanne E. – Journal of Experiential Education, 2022
Background: A common critique of adventure education research methodology is the overreliance on pre-/post-study designs to measure change. Purpose: This paper compares and contrasts two methods of data analysis on the same adventure education data set to show how these distinct approaches provide starkly different results and interpretation.…
Descriptors: Longitudinal Studies, Hierarchical Linear Modeling, Adventure Education, Educational Research
Lydia Bradford – ProQuest LLC, 2024
In randomized control trials (RCT), the recent focus has shifted to how an intervention yields positive results on its intended outcome. This aligns with the recent push of implementation science in healthcare (Bauer et al., 2015) but goes beyond this. RCTs have moved to evaluating the theoretical framing of the intervention as well as differing…
Descriptors: Hierarchical Linear Modeling, Mediation Theory, Randomized Controlled Trials, Research Design