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Vembye, Mikkel Helding; Pustejovsky, James Eric; Pigott, Therese Deocampo – Journal of Educational and Behavioral Statistics, 2023
Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we…
Descriptors: Meta Analysis, Robustness (Statistics), Statistical Analysis, Models
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Buckley, Jeffrey; Hyland, Tomás; Seery, Niall – International Journal of Technology and Design Education, 2023
Technology education research is a growing field, with the rate of growth increasing over the last 2 decades. As the field grows, it is paramount that credibility is maintained in published findings. To date there is no evidence to suggest a lack trust is warranted, however in the midst of the replication crisis there is need to ensure continued…
Descriptors: Technology Education, Educational Research, Replication (Evaluation), Credibility
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Love, Hailey R.; Fettig, Angel; Steed, Elizabeth A. – Topics in Early Childhood Special Education, 2023
Mixed methods research (MMR) has the potential to be a powerful tool to expand the ways early intervention/early childhood special education (EI/ECSE) scholarship understands and informs practice. Integration, or the purposeful combination of quantitative and qualitative research approaches, is central for rigorous MMR. However, it can be…
Descriptors: Mixed Methods Research, Qualitative Research, Statistical Analysis, Early Childhood Education
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Sims, Sam; Anders, Jake; Inglis, Matthew; Lortie-Forgues, Hugues – Journal of Research on Educational Effectiveness, 2023
Randomized controlled trials have proliferated in education, in part because they provide an unbiased estimator for the causal impact of interventions. It is increasingly recognized that many such trials in education have low power to detect an effect if indeed there is one. However, it is less well known that low powered trials tend to…
Descriptors: Randomized Controlled Trials, Educational Research, Effect Size, Intervention
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Goretzko, David – Educational and Psychological Measurement, 2022
Determining the number of factors in exploratory factor analysis is arguably the most crucial decision a researcher faces when conducting the analysis. While several simulation studies exist that compare various so-called factor retention criteria under different data conditions, little is known about the impact of missing data on this process.…
Descriptors: Factor Analysis, Research Problems, Data, Prediction
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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
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Ranger, Jochen; Brauer, Kay – Journal of Educational and Behavioral Statistics, 2022
The generalized S-X[superscript 2]-test is a test of item fit for items with polytomous responses format. The test is based on a comparison of the observed and expected number of responses in strata defined by the test score. In this article, we make four contributions. We demonstrate that the performance of the generalized S-X[superscript 2]-test…
Descriptors: Goodness of Fit, Test Items, Statistical Analysis, Item Response Theory
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Sim, Mikyung; Kim, Su-Young; Suh, Youngsuk – Educational and Psychological Measurement, 2022
Mediation models have been widely used in many disciplines to better understand the underlying processes between independent and dependent variables. Despite their popularity and importance, the appropriate sample sizes for estimating those models are not well known. Although several approaches (such as Monte Carlo methods) exist, applied…
Descriptors: Sample Size, Statistical Analysis, Predictor Variables, Path Analysis
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Wang, Weimeng; Liu, Yang; Liu, Hongyun – Journal of Educational and Behavioral Statistics, 2022
Differential item functioning (DIF) occurs when the probability of endorsing an item differs across groups for individuals with the same latent trait level. The presence of DIF items may jeopardize the validity of an instrument; therefore, it is crucial to identify DIF items in routine operations of educational assessment. While DIF detection…
Descriptors: Test Bias, Test Items, Equated Scores, Regression (Statistics)
Bonifay, Wes – Grantee Submission, 2022
Traditional statistical model evaluation typically relies on goodness-of-fit testing and quantifying model complexity by counting parameters. Both of these practices may result in overfitting and have thereby contributed to the generalizability crisis. The information-theoretic principle of minimum description length addresses both of these…
Descriptors: Statistical Analysis, Models, Goodness of Fit, Evaluation Methods
Daniel McNeish; Jeffrey R. Harring; Daniel J. Bauer – Grantee Submission, 2022
Growth mixture models (GMMs) are a popular method to identify latent classes of growth trajectories. One shortcoming of GMMs is nonconvergence, which often leads researchers to apply covariance equality constraints to simplify estimation, though this may be a dubious assumption. Alternative model specifications have been proposed to reduce…
Descriptors: Growth Models, Classification, Accuracy, Sample Size
Wendy Chan; Larry Vernon Hedges – Journal of Educational and Behavioral Statistics, 2022
Multisite field experiments using the (generalized) randomized block design that assign treatments to individuals within sites are common in education and the social sciences. Under this design, there are two possible estimands of interest and they differ based on whether sites or blocks have fixed or random effects. When the average treatment…
Descriptors: Research Design, Educational Research, Statistical Analysis, Statistical Inference
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Mehrdad Vasheghani Farahani; Zahra Ghane – Australian Journal of Language and Literacy, 2022
Discourse markers can have various functions depending on the context in which they are used. Taking this into consideration, in this corpus-based research, we analyzed and unveiled quantitatively and qualitatively the functions of four discourse markers in academic spoken English. To this purpose, four discourse markers, i.e., "I mean,"…
Descriptors: Oral English, Language Styles, Discourse Modes, Academic Language
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John J. Posillico; David J. Edwards – Industry and Higher Education, 2024
Purpose: Higher education curriculum development in the construction industry has historically received scant academic attention and often, courses/programmes are largely developed using the tacit knowledge of individual tutors. This research investigates the core interpersonal and technical skills and competencies required of a contemporary…
Descriptors: Physical Environment, Construction Management, Higher Education, Curriculum Development
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Daniel Seddig – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The latent growth model (LGM) is a popular tool in the social and behavioral sciences to study development processes of continuous and discrete outcome variables. A special case are frequency measurements of behaviors or events, such as doctor visits per month or crimes committed per year. Probability distributions for such outcomes include the…
Descriptors: Growth Models, Statistical Analysis, Structural Equation Models, Crime
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