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Beth Chance; Karen McGaughey; Sophia Chung; Alex Goodman; Soma Roy; Nathan Tintle – Journal of Statistics and Data Science Education, 2025
"Simulation-based inference" is often considered a pedagogical strategy for helping students develop inferential reasoning, for example, giving them a visual and concrete reference for deciding whether the observed statistic is unlikely to happen by chance alone when the null hypothesis is true. In this article, we highlight for teachers…
Descriptors: Simulation, Sampling, Randomized Controlled Trials, Hypothesis Testing
Andrew Jaciw – Society for Research on Educational Effectiveness, 2024
Background: Rooted in problems of social justice, intersectionality addresses intragroup differences in impacts and outcomes and the compound discrimination at specific intersections of classification (Crenshaw,1991). It stresses that deficits/debts in outcomes often occur non-additively; for example, discriminatory hiring practices can be…
Descriptors: Intersectionality, Classification, Randomized Controlled Trials, Factor Analysis
Yi, Zhiyao; Chen, Yi-Hsin; Yin, Yue; Cheng, Ke; Wang, Yan; Nguyen, Diep; Pham, Thanh; Kim, EunSook – Journal of Experimental Education, 2022
A simulation study was conducted to examine the efficacy of nine frequently-used HOV tests, including Levene's tests with squared residuals and with absolute residuals, Brown and Forsythe (BF) test, Bootstrap BF test, O'Brien test, Z-variance test, Box-Scheffé (BS) test, Bartlett test, and Pseudo jackknife test under comprehensive simulation…
Descriptors: Statistical Analysis, Robustness (Statistics), Sampling, Statistical Inference
Wendy Chan; Jimin Oh; Chen Li; Jiexuan Huang; Yeran Tong – Society for Research on Educational Effectiveness, 2023
Background: The generalizability of a study's results continues to be at the forefront of concerns in evaluation research in education (Tipton & Olsen, 2018). Over the past decade, statisticians have developed methods, mainly based on propensity scores, to improve generalizations in the absence of random sampling (Stuart et al., 2011; Tipton,…
Descriptors: Generalizability Theory, Probability, Scores, Sampling
Meng Qiu; Ke-Hai Yuan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Latent class analysis (LCA) is a widely used technique for detecting unobserved population heterogeneity in cross-sectional data. Despite its popularity, the performance of LCA is not well understood. In this study, we evaluate the performance of LCA with binary data by examining classification accuracy, parameter estimation accuracy, and coverage…
Descriptors: Classification, Sample Size, Monte Carlo Methods, Social Science Research
Diego Cortes; Dirk Hastedt; Sabine Meinck – Large-scale Assessments in Education, 2025
This paper informs users of data collected in international large-scale assessments (ILSA), by presenting argumentsunderlining the importance of considering two design features employed in these studies. We examine a commonmisconception stating that the uncertainty arising from the assessment design is negligible compared with that arisingfrom the…
Descriptors: Sampling, Research Design, Educational Assessment, Statistical Inference
Sarah E. Robertson; Jon A. Steingrimsson; Issa J. Dahabreh – Evaluation Review, 2024
When planning a cluster randomized trial, evaluators often have access to an enumerated cohort representing the target population of clusters. Practicalities of conducting the trial, such as the need to oversample clusters with certain characteristics in order to improve trial economy or support inferences about subgroups of clusters, may preclude…
Descriptors: Randomized Controlled Trials, Generalization, Inferences, Hierarchical Linear Modeling
Marianne van Dijke-Droogers; Paul Drijvers; Arthur Bakker – Mathematics Education Research Journal, 2025
In our data-driven society, it is essential for students to become statistically literate. A core domain within Statistical Literacy is Statistical Inference, the ability to draw inferences from sample data. Acquiring and applying inferences is difficult for students and, therefore, usually not included in the pre-10th-grade curriculum. However,…
Descriptors: Statistical Inference, Learning Trajectories, Grade 9, High School Students
Avery H. Closser; Adam Sales; Anthony F. Botelho – Grantee Submission, 2024
Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data on study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…
Descriptors: Data Analysis, Educational Research, Randomized Controlled Trials, Sampling
Avery H. Closser; Adam Sales; Anthony F. Botelho – Educational Technology Research and Development, 2024
Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data to study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…
Descriptors: Data Analysis, Educational Research, Randomized Controlled Trials, Sampling
Weber, Frank; Knapp, Guido; Glass, Änne; Kundt, Günther; Ickstadt, Katja – Research Synthesis Methods, 2021
There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study…
Descriptors: Meta Analysis, Computation, Intervals, Statistical Analysis
Lee, Hyung Rock; Sung, Jaeyun; Lee, Sunbok – International Journal of Assessment Tools in Education, 2021
Conventional estimators for indirect effects using a difference in coefficients and product of coefficients produce the same results for continuous outcomes. However, for binary outcomes, the difference in coefficient estimator systematically underestimates the indirect effects because of a scaling problem. One solution is to standardize…
Descriptors: Statistical Analysis, Computation, Regression (Statistics), Scaling
Korkman, Hamdi; Tekel, Esra – International Journal of Contemporary Educational Research, 2020
The aim of the study is to examine the mediating role of empathy in the relationship between rational and experiential thinking styles and was designed in a correlational design. The sample of the study consists of 593 university students who were determined by simple random sampling method. Emotional Intelligence Questionnaire--Short Form,…
Descriptors: Empathy, Emotional Intelligence, Cognitive Style, College Students
Anqi Zhao; Peng Ding; Tirthankar Dasgupta – Grantee Submission, 2018
Given two 2-level factors of interest, a 2[superscript 2] split-plot design (a) takes each of the 2 [superscript 2] = 4 possible factorial combinations as a treatment, (b) identifies one factor as `whole-plot,' (c) divides the experimental units into blocks, and (d) assigns the treatments in such away that all units within the same block receive…
Descriptors: Statistical Inference, Computation, Statistical Analysis, Sampling
Köhler, Carmen; Robitzsch, Alexander; Hartig, Johannes – Journal of Educational and Behavioral Statistics, 2020
Testing whether items fit the assumptions of an item response theory model is an important step in evaluating a test. In the literature, numerous item fit statistics exist, many of which show severe limitations. The current study investigates the root mean squared deviation (RMSD) item fit statistic, which is used for evaluating item fit in…
Descriptors: Test Items, Goodness of Fit, Statistics, Bias