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Josh Leung-Gagné; Sean F. Reardon – Grantee Submission, 2023
Recent studies have shown that U.S. Census-- and American Community Survey (ACS)--based estimates of income segregation are subject to upward finite sampling bias (Logan et al. 2018; Logan et al. 2020; Reardon et al. 2018). We identify two additional sources of bias that are larger and opposite in sign to finite sampling bias: measurement…
Descriptors: Income, Low Income Groups, Social Bias, Statistical Bias
Wang, Shiyu; Xiao, Houping; Cohen, Allan – Journal of Educational and Behavioral Statistics, 2021
An adaptive weight estimation approach is proposed to provide robust latent ability estimation in computerized adaptive testing (CAT) with response revision. This approach assigns different weights to each distinct response to the same item when response revision is allowed in CAT. Two types of weight estimation procedures, nonfunctional and…
Descriptors: Computer Assisted Testing, Adaptive Testing, Computation, Robustness (Statistics)
Magdalena Bennett – Society for Research on Educational Effectiveness, 2021
Introduction: Differences-in-Differences (DD) is a commonly-used approach in policy evaluation for identifying the impact of an intervention or treatment. Under a parallel trend assumption (PTA), we can recover a causal effect by comparing the difference in outcomes between a treatment and a control group, both before and after an intervention was…
Descriptors: Educational Vouchers, Preferences, School Segregation, Program Evaluation
Du, Han; Enders, Craig; Keller, Brian; Bradbury, Thomas N.; Karney, Benjamin R. – Grantee Submission, 2022
Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…
Descriptors: Bayesian Statistics, Data Analysis, Computer Simulation, Sample Size
Slez, Adam – Sociological Methods & Research, 2019
Young and Holsteen (YH) introduce a number of tools for evaluating model uncertainty. In so doing, they are careful to differentiate their method from existing forms of model averaging. The fundamental difference lies in the way in which the underlying estimates are weighted. Whereas standard approaches to model averaging assign higher weight to…
Descriptors: Research Methodology, Models, Ambiguity (Context), Computation
Chu-Yang Chang; Hsu-Chan Kuo – Education and Information Technologies, 2025
The rapid advancement of educational technologies in recent decades has underscored the increasing importance of digital literacy (DL) as a core competency for all students, as recognised in various educational policies and programs. Evaluating students' DL is crucial for providing valuable insights to guide future educational initiatives. This…
Descriptors: Digital Literacy, Questionnaires, Test Construction, Test Validity
Deng, Lifang; Yuan, Ke-Hai – Grantee Submission, 2022
Structural equation modeling (SEM) has been deemed as a proper method when variables contain measurement errors. In contrast, path analysis with composite-scores is preferred for prediction and diagnosis of individuals. While path analysis with composite-scores has been criticized for yielding biased parameter estimates, recent literature pointed…
Descriptors: Structural Equation Models, Path Analysis, Weighted Scores, Error of Measurement
Zachary J. Roman; Patrick Schmidt; Jason M. Miller; Holger Brandt – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Careless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading to erroneous inference. There are multiple approaches to identifying and accounting for C/IER in survey settings, of these approaches the best performing…
Descriptors: Structural Equation Models, Bayesian Statistics, Response Style (Tests), Robustness (Statistics)
Edoardo G. Ostinelli; Orestis Efthimiou; Yan Luo; Clara Miguel; Eirini Karyotaki; Pim Cuijpers; Toshi A. Furukawa; Georgia Salanti; Andrea Cipriani – Research Synthesis Methods, 2024
When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the…
Descriptors: Network Analysis, Meta Analysis, Depression (Psychology), Regression (Statistics)
Selcuk Acar; Lindsay E. Lee; Jaret Hodges – Creativity Research Journal, 2023
Numerous primary studies and a recent meta-analytic confirmatory factor analysis (Meta-CFA; Said-Metwaly, Fernández-Castilla, Kyndt, & Van den Noortgate, 2018) have shown that Torrance Tests of Creative Thinking -- Figural (TTCT-F) consists of two factors. However, recent research has raised questions regarding factor analysis of the TTCT-F…
Descriptors: Creativity, Creative Thinking, Creativity Tests, Factor Structure
Peter Organisciak; Selcuk Acar; Denis Dumas; Kelly Berthiaume – Grantee Submission, 2023
Automated scoring for divergent thinking (DT) seeks to overcome a key obstacle to creativity measurement: the effort, cost, and reliability of scoring open-ended tests. For a common test of DT, the Alternate Uses Task (AUT), the primary automated approach casts the problem as a semantic distance between a prompt and the resulting idea in a text…
Descriptors: Automation, Computer Assisted Testing, Scoring, Creative Thinking
Ruben Trigueros; Alejandro García-Mas – British Journal of Educational Psychology, 2025
Introduction: In recent years, the incorporation of novelty as a psychological need and the study of the frustration of needs have become a recurring theme in the research on psychological needs in the educational environment. Currently, there are two scales available to assess the frustration of basic psychological needs (FBN) in the context of…
Descriptors: Psychological Patterns, Well Being, Resilience (Psychology), Self Determination
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
Ranger, Jochen; Kuhn, Jörg-Tobias; Wolgast, Anett – Journal of Educational Measurement, 2021
Van der Linden's hierarchical model for responses and response times can be used in order to infer the ability and mental speed of test takers from their responses and response times in an educational test. A standard approach for this is maximum likelihood estimation. In real-world applications, the data of some test takers might be partly…
Descriptors: Models, Reaction Time, Item Response Theory, Tests
Craig K. Enders – Grantee Submission, 2023
The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of "Psychological Methods." Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of…
Descriptors: Data, Research, Theories, Regression (Statistics)

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