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Edmonds, Bruce – International Journal of Social Research Methodology, 2023
This paper looks at the tension between the desire to claim predictive ability for Agent-Based Models (ABMs) and its extreme difficulty for social and ecological systems, suggesting that this is the main cause for the continuance of a rhetoric of prediction that is at odds with what is achievable. Following others, it recommends that it is better…
Descriptors: Models, Prediction, Evaluation Methods, Standards
Zeyuan Jing – ProQuest LLC, 2023
This dissertation presents a comprehensive review of the evolution of DIF analysis within educational measurement from the 1980s to the present. The review elucidates the concept of DIF, particularly emphasizing the crucial role of grouping for exhibiting DIF. Then, the dissertation introduces an innovative modification to the newly developed…
Descriptors: Item Response Theory, Algorithms, Measurement, Test Bias
Sy Han Chiou; Gongjun Xu; Jun Yan; Chiung-Yu Huang – Grantee Submission, 2023
Recurrent event analyses have found a wide range of applications in biomedicine, public health, and engineering, among others, where study subjects may experience a sequence of event of interest during follow-up. The R package reReg offers a comprehensive collection of practical and easy-to-use tools for regression analysis of recurrent events,…
Descriptors: Data Analysis, Computer Software, Regression (Statistics), Models
Hans-Peter Piepho; Johannes Forkman; Waqas Ahmed Malik – Research Synthesis Methods, 2024
Checking for possible inconsistency between direct and indirect evidence is an important task in network meta-analysis. Recently, an evidence-splitting (ES) model has been proposed, that allows separating direct and indirect evidence in a network and hence assessing inconsistency. A salient feature of this model is that the variance for…
Descriptors: Maximum Likelihood Statistics, Evidence, Networks, Meta Analysis
Brinley N. Zabriskie; Nolan Cole; Jacob Baldauf; Craig Decker – Research Synthesis Methods, 2024
Meta-analyses have become the gold standard for synthesizing evidence from multiple clinical trials, and they are especially useful when outcomes are rare or adverse since individual trials often lack sufficient power to detect a treatment effect. However, when zero events are observed in one or both treatment arms in a trial, commonly used…
Descriptors: Meta Analysis, Error Correction, Computation, Simulation
Philip C. Duczyminski – ProQuest LLC, 2024
Firefighters face many high-risk situations, from battling fires to managing hazardous materials and medical emergencies. The inherent dangers of these scenarios are reflected in the statistics from the U.S. Fire Administration, which reported 141 on-duty firefighter fatalities in 2021. Recognizing the critical need for enhanced safety, the…
Descriptors: Fire Protection, Job Training, Simulation, Instructional Effectiveness
Guido Schwarzer; Gerta Rücker; Cristina Semaca – Research Synthesis Methods, 2024
The "LFK" index has been promoted as an improved method to detect bias in meta-analysis. Putatively, its performance does not depend on the number of studies in the meta-analysis. We conducted a simulation study, comparing the "LFK" index test to three standard tests for funnel plot asymmetry in settings with smaller or larger…
Descriptors: Bias, Meta Analysis, Simulation, Evaluation Methods
John Mart V. DelosReyes; Miguel A. Padilla – Journal of Experimental Education, 2024
Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…
Descriptors: Research Problems, Correlation, Intervals, Computation
Tihomir Asparouhov; Bengt Muthén – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Penalized structural equation models (PSEM) is a new powerful estimation technique that can be used to tackle a variety of difficult structural estimation problems that can not be handled with previously developed methods. In this paper we describe the PSEM framework and illustrate the quality of the method with simulation studies.…
Descriptors: Structural Equation Models, Computation, Factor Analysis, Measurement Techniques
Jihong Zhang; Jonathan Templin; Xinya Liang – Journal of Educational Measurement, 2024
Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…
Descriptors: Bayesian Statistics, Cognitive Measurement, Models, Classification
Harry May; Travis Atkison – Journal of Cybersecurity Education, Research and Practice, 2024
Detecting and mitigating wormhole attacks in wireless networks remains a critical challenge due to their deceptive nature and potential to compromise network integrity. This paper proposes a novel approach to wormhole detection by leveraging propagation delay analysis between network nodes. Unlike traditional methods that rely on signature-based…
Descriptors: Computer Security, Identification, Computer Networks, Telecommunications
Alexander Robitzsch; Oliver Lüdtke – Structural Equation Modeling: A Multidisciplinary Journal, 2025
The random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes. In a recent study, Bailey et al. demonstrated through a simulation study that the between-person variance components in the RICLPM can occur only due…
Descriptors: Longitudinal Studies, Correlation, Time, Simulation
Ye Ma; Deborah J. Harris – Educational Measurement: Issues and Practice, 2025
Item position effect (IPE) refers to situations where an item performs differently when it is administered in different positions on a test. The majority of previous research studies have focused on investigating IPE under linear testing. There is a lack of IPE research under adaptive testing. In addition, the existence of IPE might violate Item…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
Jean-Paul Fox – Journal of Educational and Behavioral Statistics, 2025
Popular item response theory (IRT) models are considered complex, mainly due to the inclusion of a random factor variable (latent variable). The random factor variable represents the incidental parameter problem since the number of parameters increases when including data of new persons. Therefore, IRT models require a specific estimation method…
Descriptors: Sample Size, Item Response Theory, Accuracy, Bayesian Statistics
Tugay Kaçak; Abdullah Faruk Kiliç – International Journal of Assessment Tools in Education, 2025
Researchers continue to choose PCA in scale development and adaptation studies because it is the default setting and overestimates measurement quality. When PCA is utilized in investigations, the explained variance and factor loadings can be exaggerated. PCA, in contrast to the models given in the literature, should be investigated in…
Descriptors: Factor Analysis, Monte Carlo Methods, Mathematical Models, Sample Size