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Tabron, Lolita A.; Thomas, Amanda K. – Review of Educational Research, 2023
Although the critical research cannon is often associated with qualitative scholars, there is a growing number of critical scholars who are refusing positivist-informed quantitative analyses. However, as a growing number of education scholars engaged in critical approaches to quantitative inquiry, instances of conflation began to surface. We…
Descriptors: Literature Reviews, Statistical Analysis, Educational Research, Critical Theory
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Maksimovic, Jelena; Evtimov, Jelena – Research in Pedagogy, 2023
The paradigm on which a methodological approach is developed determines the situations in which its application will be most appropriate. The quantitative approach implies a positivist paradigm, the basis of which is cause-and-effect relationships, as well as the questioning and verifying of existing theories. Positivism aims to prove that…
Descriptors: Statistical Analysis, Research Methodology, Educational Research, Models
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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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Donald Secreast – CEA Forum, 2023
"Using Sentiment Analysis to Ease Students toward or around Macroanalysis" introduces teachers to the mathematical analytical method currently being promoted by Matthew Jockers which he calls macroanalysis. This method uses an algorithm called "R," originally designed by researchers in sociology. In many ways, macroanalysis…
Descriptors: Literary Criticism, Statistical Analysis, Algorithms, Computer Uses in Education
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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
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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
Kenneth A. Frank; Qinyun Lin; Ran Xu; Spiro Maroulis; Anna Mueller – Grantee Submission, 2023
Social scientists seeking to inform policy or public action must carefully consider how to identify effects and express inferences because actions based on invalid inferences will not yield the intended results. Recognizing the complexities and uncertainties of social science, we seek to inform inevitable debates about causal inferences by…
Descriptors: Social Sciences, Research Methodology, Statistical Inference, Robustness (Statistics)
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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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Kalkbrenner, Michael T. – Professional Counselor, 2022
Conducting and publishing rigorous empirical research based on original data is essential for advancing and sustaining high-quality counseling practice. The purpose of this article is to provide a one-stop-shop for writing a rigorous quantitative Methods section in counseling and related fields. The importance of judiciously planning,…
Descriptors: Guidelines, Statistical Analysis, Research Methodology, Counseling
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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)
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