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Muhammad Aslam – Measurement: Interdisciplinary Research and Perspectives, 2025
The existing algorithm employing the log-normal distribution lacks applicability in generating imprecise data. This paper addresses this limitation by first introducing the log-normal distribution as a means to handle imprecise data. Subsequently, we leverage the neutrosophic log-normal distribution to devise an algorithm specifically tailored for…
Descriptors: Statistical Distributions, Algorithms, Sampling
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Juan F. Muñoz; Pablo J. Moya-Fernández; Encarnación Álvarez-Verdejo – Sociological Methods & Research, 2025
The Gini index is probably the most commonly used indicator to measure inequality. For continuous distributions, the Gini index can be computed using several equivalent formulations. However, this is not the case with discrete distributions, where controversy remains regarding the expression to be used to estimate the Gini index. We attempt to…
Descriptors: Bias, Educational Indicators, Equal Education, Monte Carlo Methods
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Adrian Quintero; Emmanuel Lesaffre; Geert Verbeke – Journal of Educational and Behavioral Statistics, 2024
Bayesian methods to infer model dimensionality in factor analysis generally assume a lower triangular structure for the factor loadings matrix. Consequently, the ordering of the outcomes influences the results. Therefore, we propose a method to infer model dimensionality without imposing any prior restriction on the loadings matrix. Our approach…
Descriptors: Bayesian Statistics, Factor Analysis, Factor Structure, Sampling
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Geoffrey Walford – Ethnography and Education, 2024
It is now half a century since Joey explained to Paul Willis: 'Vandalising […] that's the opposite of boredom -- excitement, defying the law', one of many similar comments subsequently recorded in "Learning to Labour" (34). The book rapidly became an academic best-seller, and has since become an academic 'national treasure'. But, before…
Descriptors: Research Methodology, Ethnography, Books, Educational Research
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van Aert, Robbie C. M.; Goos, Cas – Research Synthesis Methods, 2023
The partial correlation coefficient quantifies the relationship between two variables while taking into account the effect of one or multiple control variables. Researchers often want to synthesize partial correlation coefficients in a meta-analysis since these can be readily computed based on the reported results of a linear regression analysis.…
Descriptors: Computation, Sampling, Correlation, Meta Analysis
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van Aert, Robbie C. M. – Research Synthesis Methods, 2023
The partial correlation coefficient (PCC) is used to quantify the linear relationship between two variables while taking into account/controlling for other variables. Researchers frequently synthesize PCCs in a meta-analysis, but two of the assumptions of the common equal-effect and random-effects meta-analysis model are by definition violated.…
Descriptors: Correlation, Meta Analysis, Sampling, Simulation
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Sabine Doebel; Michael C. Frank – Journal of Cognition and Development, 2024
Diverse samples are valuable to the study of development, and to psychology more broadly. But convenience samples--typically recruited from local populations close to universities--are still the most widely used in developmental science, despite the fact that their use leads to a vast over-representation of Western, White, and high socio-economic…
Descriptors: Sampling, Psychology, Recruitment, Research Problems
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van der Linden, Wim J. – Journal of Educational and Behavioral Statistics, 2022
The current literature on test equating generally defines it as the process necessary to obtain score comparability between different test forms. The definition is in contrast with Lord's foundational paper which viewed equating as the process required to obtain comparability of measurement scale between forms. The distinction between the notions…
Descriptors: Equated Scores, Test Items, Scores, Probability
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Chan, Wendy – American Journal of Evaluation, 2022
Over the past ten years, propensity score methods have made an important contribution to improving generalizations from studies that do not select samples randomly from a population of inference. However, these methods require assumptions and recent work has considered the role of bounding approaches that provide a range of treatment impact…
Descriptors: Probability, Scores, Scoring, Generalization
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Feldman, Hannah R. – Australian Journal of Environmental Education, 2022
The "School Strike 4 Climate" is a timely opportunity for education and research sectors to support youth stories in climate change policy, and foster impactful relationships between researchers, teachers and students. But much research in this space has inherent selection biases where youth representation in research is limited by place…
Descriptors: Strikes, Climate, Activism, Youth
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Shen, Zuchao; Kelcey, Benjamin – Journal of Experimental Education, 2022
Optimal design of multisite randomized trials leverages sampling costs to optimize sampling ratios and ultimately identify more efficient and powerful designs. Past implementations of the optimal design framework have assumed that costs of sampling units are equal across treatment conditions. In this study, we developed a more flexible optimal…
Descriptors: Randomized Controlled Trials, Sampling, Research Design, Statistical Analysis
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John R. Donoghue; Carol Eckerly – Applied Measurement in Education, 2024
Trend scoring constructed response items (i.e. rescoring Time A responses at Time B) gives rise to two-way data that follow a product multinomial distribution rather than the multinomial distribution that is usually assumed. Recent work has shown that the difference in sampling model can have profound negative effects on statistics usually used to…
Descriptors: Scoring, Error of Measurement, Reliability, Scoring Rubrics
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DeLuca, Stefanie – Sociological Methods & Research, 2023
Increasingly, the broader public, media and policymakers are looking to qualitative research to provide answers to our most pressing social questions. While an exciting and perhaps overdue moment for qualitative researchers, it is also a time when the method is coming under increasing scrutiny for a lack of reliability and transparency. The…
Descriptors: Qualitative Research, Reliability, Standards, Participant Observation
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Thorpe, Karen; Houen, Sandy; Rankin, Peter; Pattinson, Cassandra; Staton, Sally – Australian Educational Researcher, 2023
Internationally, standard observational measures of Early Childhood Education and Care (ECEC) are used to assess the quality of provision. They are applied as research tools but, significantly, also guide policy decisions, distribution of resources and public opinion. Considerable faith is placed in such measures, yet their validity, reliability…
Descriptors: Foreign Countries, Educational Quality, Classroom Environment, Measures (Individuals)
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Castellano, Katherine E.; McCaffrey, Daniel F.; Lockwood, J. R. – Journal of Educational Measurement, 2023
The simple average of student growth scores is often used in accountability systems, but it can be problematic for decision making. When computed using a small/moderate number of students, it can be sensitive to the sample, resulting in inaccurate representations of growth of the students, low year-to-year stability, and inequities for…
Descriptors: Academic Achievement, Accountability, Decision Making, Computation
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