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Luke Keele; Matthew Lenard; Lindsay Page – Journal of Research on Educational Effectiveness, 2024
In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…
Descriptors: Intervention, Cluster Grouping, Observation, Catholic Schools
Cox, Kyle; Kelcey, Benjamin – American Journal of Evaluation, 2023
Analysis of the differential treatment effects across targeted subgroups and contexts is a critical objective in many evaluations because it delineates for whom and under what conditions particular programs, therapies or treatments are effective. Unfortunately, it is unclear how to plan efficient and effective evaluations that include these…
Descriptors: Statistical Analysis, Research Design, Cluster Grouping, Sample Size
Karun Adusumilli; Francesco Agostinelli; Emilio Borghesan – National Bureau of Economic Research, 2024
This paper examines the scalability of the results from the Tennessee Student-Teacher Achievement Ratio (STAR) Project, a prominent educational experiment. We explore how the misalignment between the experimental design and the econometric model affects researchers' ability to learn about the intervention's scalability. We document heterogeneity…
Descriptors: Class Size, Research Design, Educational Research, Program Effectiveness
Menglin Xu; Jessica A. R. Logan – Educational and Psychological Measurement, 2024
Research designs that include planned missing data are gaining popularity in applied education research. These methods have traditionally relied on introducing missingness into data collections using the missing completely at random (MCAR) mechanism. This study assesses whether planned missingness can also be implemented when data are instead…
Descriptors: Research Design, Research Methodology, Monte Carlo Methods, Statistical Analysis
McKay, Brad; Corson, Abbey; Vinh, Mary-Anne; Jeyarajan, Gianna; Tandon, Chitrini; Brooks, Hugh; Hubley, Julie; Carter, Michael J. – Journal of Motor Learning and Development, 2023
A priori power analyses can ensure studies are unlikely to miss interesting effects. Recent metascience has suggested that kinesiology research may be underpowered and selectively reported. Here, we examined whether power analyses are being used to ensure informative studies in motor behavior. We reviewed every article published in three motor…
Descriptors: Incidence, Statistical Analysis, Psychomotor Skills, Motor Development
Larry V. Hedges; William R. Shadish; Prathiba Natesan Batley – Grantee Submission, 2022
Currently the design standards for single case experimental designs (SCEDs) are based on validity considerations as prescribed by the What Works Clearinghouse. However, there is a need for design considerations such as power based on statistical analyses. We compute and derive power using computations for (AB)[superscript k] designs with multiple…
Descriptors: Statistical Analysis, Research Design, Computation, Case Studies
Prathiba Natesan Batley; Madhav Thamaran; Larry Vernon Hedges – Grantee Submission, 2023
Single case experimental designs are an important research design in behavioral and medical research. Although there are design standards prescribed by the What Works Clearinghouse for single case experimental designs, these standards do not include statistically derived power computations. Recently we derived the equations for computing power for…
Descriptors: Calculators, Computer Oriented Programs, Computation, Research Design
Clintin P. Davis-Stober; Jason Dana; David Kellen; Sara D. McMullin; Wes Bonifay – Grantee Submission, 2023
Conducting research with human subjects can be difficult because of limited sample sizes and small empirical effects. We demonstrate that this problem can yield patterns of results that are practically indistinguishable from flipping a coin to determine the direction of treatment effects. We use this idea of random conclusions to establish a…
Descriptors: Research Methodology, Sample Size, Effect Size, Hypothesis Testing
Eric C. Hedberg – Grantee Submission, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
E. C. Hedberg – American Journal of Evaluation, 2023
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical…
Descriptors: Statistical Analysis, Multivariate Analysis, Randomized Controlled Trials, Research Design
Jane E. Miller – Numeracy, 2023
Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…
Descriptors: Statistical Significance, Holistic Approach, Statistical Inference, Effect Size
López-López, José A.; Page, Matthew J.; Lipsey, Mark W.; Higgins, Julian P. T. – Research Synthesis Methods, 2018
Systematic reviews often encounter primary studies that report multiple effect sizes based on data from the same participants. These have the potential to introduce statistical dependency into the meta-analytic data set. In this paper, we provide a tutorial on dealing with effect size multiplicity within studies in the context of meta-analyses of…
Descriptors: Effect Size, Literature Reviews, Meta Analysis, Research Methodology
Taylor, Joseph A.; Kowalski, Susan M.; Polanin, Joshua R.; Askinas, Karen; Stuhlsatz, Molly A. M.; Wilson, Christopher D.; Tipton, Elizabeth; Wilson, Sandra Jo – AERA Open, 2018
A priori power analyses allow researchers to estimate the number of participants needed to detect the effects of an intervention. However, power analyses are only as valid as the parameter estimates used. One such parameter, the expected effect size, can vary greatly depending on several study characteristics, including the nature of the…
Descriptors: Science Education, Statistical Analysis, Effect Size, Intervention
Swan, Daniel M.; Pustejovsky, James E. – Grantee Submission, 2018
Single-case designs are a class of repeated measures experiments used to evaluate the effects of interventions for small or specialized populations, such as individuals with low-incidence disabilities. There has been growing interest in systematic reviews and syntheses of evidence from single-case designs, but there remains a need to further…
Descriptors: Research Design, Intervention, Effect Size, Statistical Analysis
Wolfe, Katie; Dickenson, Tammiee S.; McGrath, Kathleen Virginia; Miller, Bridget – AERA Online Paper Repository, 2017
Although visual analysis has been the primary method of analysis in single-case designs (SCD), numerous statistical analyses have been developed to quantify SCD intervention effects and enable SCDs to be included in evidence-based practice reviews. This study investigated the correspondence between expert visual analysis and three effect sizes for…
Descriptors: Research Design, Statistical Analysis, Effect Size, Graphs