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Yan Xia; Selim Havan – Educational and Psychological Measurement, 2024
Although parallel analysis has been found to be an accurate method for determining the number of factors in many conditions with complete data, its application under missing data is limited. The existing literature recommends that, after using an appropriate multiple imputation method, researchers either apply parallel analysis to every imputed…
Descriptors: Data Interpretation, Factor Analysis, Statistical Inference, Research Problems
Sun Yee Yip – International Journal of Research & Method in Education, 2024
This paper draws on my experiences as a doctoral student undertaking a project to examine the professional adaptation of Asian immigrant teachers in Australia. Using a reflexive narrative approach, I examine how my position influenced my access to participants, the understanding of their contexts, and the nature of my relationship and interaction…
Descriptors: Foreign Countries, Asians, Immigrants, Teachers
Jiang Li; Chen Zhu; Mark Goh – Research Evaluation, 2025
Data Envelopment Analysis (DEA) is a widely adopted non-parametric technique for evaluating R&D performance. However, traditional DEA models often struggle to provide reliable solutions in the presence of data uncertainty. To address this limitation, this study develops a novel robust super-efficiency DEA approach to evaluate R&D…
Descriptors: Foreign Countries, Research and Development, COVID-19, Pandemics
Adrian Adams; Lauren Barth-Cohen – CBE - Life Sciences Education, 2024
In undergraduate research settings, students are likely to encounter anomalous data, that is, data that do not meet their expectations. Most of the research that directly or indirectly captures the role of anomalous data in research settings uses post-hoc reflective interviews or surveys. These data collection approaches focus on recall of past…
Descriptors: Undergraduate Students, Physics, Science Instruction, Laboratory Experiments
Walsh, Cole; Stein, Martin M.; Tapping, Ryan; Smith, Emily M.; Holmes, N. G. – Physical Review Physics Education Research, 2021
Omitted variable bias occurs in most statistical models. Whenever a confounding variable that is correlated with both dependent and independent variables is omitted from a statistical model, estimated effects of included variables are likely to be biased due to omitted variables. This issue is particularly problematic in physics education research…
Descriptors: Physics, Science Education, Educational Research, Statistical Bias
Luke Keele; Matthew Lenard; Lindsay Page – Annenberg Institute for School Reform at Brown University, 2021
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: Cluster Grouping, Educational Environment, Outcomes of Treatment, Compliance (Psychology)
Heslop, Jo; Tamez, Lucia Quintero; Parkes, Jenny – Institute of Education - London, 2021
While violence against children (VAC) has been a long-established global concern, more recently attention has been drawn to how violence occurs in and around schools (VACS) and the role of education in preventing and responding to violence. Whilst awareness about VACS is growing, more robust data are needed to inform policy and practice. Concerns…
Descriptors: Violence, Children, School Violence, Bullying