Article
Social Sciences, Mathematical Methods
Stephanie Eckman, Jennifer Unangst, Jill A. Dever, Christopher Antoun
Summary: Survey data producers provide estimates of nonresponse bias in released or analyzed data, but few studies acknowledge that these estimates vary across samples. Using simulations, the study shows that low response rates and clustering increase the variability of bias estimates. Three methods to estimate the sampling variance of nonresponse bias are evaluated, and linearization and replication methods perform well with all studied populations.
JOURNAL OF SURVEY STATISTICS AND METHODOLOGY
(2023)
Article
Construction & Building Technology
Abbas Babazadeh, Mohammad Jafari
Summary: This study proposed a new method using logistic regression analysis to estimate the required percentage of additives for improving asphalt binder performance, showing that Superpave integer grades may overestimate the additive percentage and perform poorly when the pavement temperature is far below the next higher grade. The suggested alternative method based on fitted logistic models provides estimations at very strong confidence levels.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Samuel Rosa, Andrea Kocianova
Summary: This paper addresses the issue of accuracy in estimating critical gaps at unsignalized intersections, providing new methods for measuring the accuracy of such estimates and offering guidance on the number of observations required for reliable results.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Construction & Building Technology
Xiang Xu, Zhen-Dong Qian, Qiao Huang, Yuan Ren, Bin Liu
Summary: A probabilistic approach based on confidence interval estimation is developed to assess uncertainties in anomaly detection for large span cable-supported bridges. By preprocessing raw signals, extracting an energy index, and using confidence interval estimation, anomalies such as spikes, overloading vehicles, and snow disasters are successfully detected.
ADVANCES IN STRUCTURAL ENGINEERING
(2022)
Article
Economics
Giuseppe Bertola
Summary: The amount of learning effort required to pass an imprecise exam decreases as the exam becomes more precise, and especially when the failure probability approaches zero. If the distribution of measurement errors follows a normal distribution, maximum effort is exerted when precision leads to a failure probability of around 16%.
Article
Medical Laboratory Technology
Kelly A. Devereaux, Rhona J. Souers, Rondell P. Graham, Bryce P. Portier, Lea F. Surrey, Anna Yemelyanova, Patricia Vasalos, Dimitri G. Trembath, Joel T. Moncur
Summary: This study investigated the practices of neoplastic cellularity assessment domestically and internationally, and found that variations in laboratory practices can affect the accuracy of assessment. Therefore, there is a need for a consensus definition and standardization of neoplastic cellularity assessment.
ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE
(2022)
Article
Medical Laboratory Technology
Kelly A. Devereaux, Rhona J. Souers, Rondell P. Graham, Bryce P. Portier, Lea F. Surrey, Anna Yemelyanova, Patricia Vasalos, Dimitri G. Trembath, Joel T. Moncur
Summary: This study investigated the practices of neoplastic cellularity assessment both domestically and internationally, revealing variations in laboratory practices and their impact on assessment accuracy. Therefore, a consensus definition and improved standardization are needed to enhance the accuracy of neoplastic cellularity assessment.
ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE
(2022)
Article
Environmental Sciences
K. hanh Ninh Nguyen, Annarosa Quarello, Olivier Bock, Emilie Lebarbier
Summary: This study investigates the sensitivity of the GNSSseg segmentation method to various changes and found significant differences in the detection of change-points under different conditions. The newer models and reanalyses tend to improve the quality and sensitivity of the segmentation.
Article
Multidisciplinary Sciences
Omer Bobrowski, Primoz Skraba
Summary: This article reports a surprising discovery that persistence diagrams arising from random point-clouds follow a universal probability law when normalized properly. The authors reach this conclusion based on extensive experimentation on simulated and real data, encompassing point-clouds with diverse geometry, topology, and probability distributions. They also propose a new hypothesis testing framework for computing significance values for individual topological features within persistence diagrams, offering a new quantitative approach to assessing the significance of structure in data.
SCIENTIFIC REPORTS
(2023)
Article
Quantum Science & Technology
Xuan-Hoai Thi Nguyen, Mahn-Soo Choi
Summary: Direct quantum state tomography, seeking direct access to the complex values of the wave function at particular positions, extends the idea of quantum metrology to estimate complex-valued phase. It enables identification of optimal measurements and investigation of fundamental precision limit, reaching the Heisenberg limit.
QUANTUM INFORMATION PROCESSING
(2021)
Article
Computer Science, Software Engineering
Magne Jorgensen, Gunnar Rye Bergersen, Knut Liestol
Summary: This study found that for larger tasks, those with the lowest programming skill tend to give the lowest and most over-optimistic effort estimates, while for smaller tasks, individuals with the lowest skill level tend to give the highest and most over-pessimistic estimates.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2021)
Article
Computer Science, Software Engineering
Federica Sarro, Rebecca Moussa, Alessio Petrozziello, Mark Harman
Summary: This paper introduces a new approach called Learning From Mistakes (LFM) to predictive modeling for software engineering. The core idea is to learn from past estimation errors made by human experts and predict characteristics of future misestimates to improve future estimates. Through an empirical study on software projects, it is found that the type, severity, and magnitude of errors can be predicted, and utilizing these predictions can achieve significantly better estimates than traditional methods.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Software Engineering
Vali Tawosi, Federica Sarro, Alessio Petrozziello, Mark Harman
Summary: The study replicates and extends a previous research on multi-objective software effort estimation, strengthening both internal and external validity. The results confirm the superior performance of CoGEE and its effectiveness across different multi-objective algorithms.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Article
Audiology & Speech-Language Pathology
Robert H. Margolis, Richard H. Wilson, George L. Saly
Summary: Confidence levels were established to determine if a word-recognition score is within the expected range for a hearing loss group or significantly below or above. Percentiles representing scores below and above the expected range were established. These confidence levels and expected ranges may be helpful for interpreting word-recognition scores obtained with widely used test materials.
Article
Mathematical & Computational Biology
Damon M. Bayer, Michael P. Fay, Barry I. Graubard
Summary: We have developed and studied a new method for estimating disease prevalence in complex surveys with imperfect assays. Our method combines gamma intervals and sensitivity/specificity estimates to improve coverage rates. Comparisons with established methods show that our approach performs well, particularly in low prevalence scenarios.
STATISTICS IN MEDICINE
(2023)
