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Shen, Ting; Konstantopoulos, Spyros – Practical Assessment, Research & Evaluation, 2022
Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…
Descriptors: Sampling, Weighted Scores, Hierarchical Linear Modeling, Educational Research
Tamara Broderick; Andrew Gelman; Rachael Meager; Anna L. Smith; Tian Zheng – Grantee Submission, 2022
Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…
Descriptors: Taxonomy, Trust (Psychology), Algorithms, Probability
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Almquist, Zack W.; Arya, Sakshi; Zeng, Li; Spiro, Emma – Field Methods, 2019
Online platforms offer new opportunities to study human behavior. However, while social scientists are often interested in using behavioral trace data--data created by a user over the course of their everyday life--to draw inferences about users, many online platforms only allow data to be sampled based on user activities (leading to data sets…
Descriptors: Sampling, Data, Internet, Behavior
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Salim Nabhan; Anita Habók – SAGE Open, 2025
As the integration of digital technologies continues to shape academic landscapes, assessing digital literacy in the context of academic writing becomes paramount. Several instruments and frameworks are available for measuring digital literacy and examining it from different perspectives; however, none are suitable for measuring the digital…
Descriptors: Digital Literacy, Academic Language, Writing (Composition), Measures (Individuals)
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
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Shen, Zuchao; Kelcey, Benjamin – Journal of Educational and Behavioral Statistics, 2020
Conventional optimal design frameworks consider a narrow range of sampling cost structures that thereby constrict their capacity to identify the most powerful and efficient designs. We relax several constraints of previous optimal design frameworks by allowing for variable sampling costs in cluster-randomized trials. The proposed framework…
Descriptors: Sampling, Research Design, Randomized Controlled Trials, Statistical Analysis
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Zhang, Jiahui; Cogan, Leland S.; Schmidt, William H. – Educational Measurement: Issues and Practice, 2020
This study addresses measurement issues around a standards-based content analysis of mathematics textbooks' coverage of standards for use in large-scale monitoring of standards implementation as proposed in a 2013 report by the National Research Council. An earlier study produced an exhaustive content analysis of textbooks using the 2012 Common…
Descriptors: Textbook Content, Academic Standards, Mathematics Curriculum, Content Analysis
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Spencer, Elizabeth; Bryant, Lucy; Colyvas, Kim – Topics in Language Disorders, 2020
Variability is common in language sample analysis (LSA), arising from personal factors such as age or level of education, or from factors within the text such as its length and purpose. Variability can affect interpretation of results in clinical practice and research studies, as well as the ability to detect change in individuals over time. This…
Descriptors: Sampling, Language Impairments, Evaluation Methods, Evidence Based Practice
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Liu, Xiaofeng Steven; Shin, Hyejo Hailey – Teaching Statistics: An International Journal for Teachers, 2020
Computer simulation can be used to demonstrate why the unbiased sample variance uses degrees of freedom (n-1). This is first demonstrated for sampling from a normal random variable, and in additional simulations for some selected non-normal random variables, namely, chi-square and binomial.
Descriptors: Computer Simulation, Statistics, Sampling, Statistical Bias
Qu, Wen; Liu, Haiyan; Zhang, Zhiyong – Grantee Submission, 2020
In social and behavioral sciences, data are typically not normally distributed, which can invalidate hypothesis testing and lead to unreliable results when being analyzed by methods developed for normal data. The existing methods of generating multivariate non-normal data typically create data according to specific univariate marginal measures…
Descriptors: Social Science Research, Multivariate Analysis, Statistical Distributions, Monte Carlo Methods
Xinran Li; Peng Ding; Donald B. Rubin – Grantee Submission, 2020
With many pretreatment covariates and treatment factors, the classical factorial experiment often fails to balance covariates across multiple factorial effects simultaneously. Therefore, it is intuitive to restrict the randomization of the treatment factors to satisfy certain covariate balance criteria, possibly conforming to the tiers of…
Descriptors: Experiments, Research Design, Randomized Controlled Trials, Sampling
Naian Yin – ProQuest LLC, 2020
Online networks, as digital images reflecting every aspects of real world especially under the current context of information technology, have become the most massive and opulent data source these days, where vast amount of information keeps being produced and transmitted. Their rapid expansion in scale and data volume draws wide attention and…
Descriptors: Sampling, Networks, Topology, Computer Mediated Communication
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Leher Singh – Journal of Cognition and Development, 2024
This article serves as an introduction to the Special Issue on "Decolonizing and Diversifying Research in Cognitive Development." The Special Issue comprises six articles: two articles are empirical articles that focus on executive function development in under-represented environments, two articles address barriers pathways toward…
Descriptors: Decolonization, Cognitive Development, Theory Practice Relationship, Research and Development
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Seyda Ince Sezer; Mehmet Diyaddin Yasar – Science Insights Education Frontiers, 2024
The purpose of this research is to identify the situation through content analysis of scale development studies conducted by Turkish researchers in the field of preschool education. Thus, the overall trend of scale development research in preschool education was established. This research is a document analysis study. The documents studied are…
Descriptors: Foreign Countries, Preschool Education, Preschool Teachers, Measures (Individuals)
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Qian, Jiahe; Li, Shuhong – ETS Research Report Series, 2021
In recent years, harmonic regression models have been applied to implement quality control for educational assessment data consisting of multiple administrations and displaying seasonality. As with other types of regression models, it is imperative that model adequacy checking and model fit be appropriately conducted. However, there has been no…
Descriptors: Models, Regression (Statistics), Language Tests, Quality Control
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