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85 papers

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Application of Propensity Score Methods to Address Missing Data in a Trial on the Effect of Energy Protein Supplementation Among Pulmonary TB-HIV Patients in Mwanza, Tanzania

This study evaluated propensity score inverse probability weighting (PS-IPW) and multiple imputation (MI) against complete case analysis for handling monotonic missing data in a pulmonary TB-HIV supplementation trial in Tanzania, finding that while both advanced methods outperformed traditional analysis in bias and efficiency, none revealed statistically significant treatment effects.

Auson B. Magige, Benson Kidenya, Jeremiah Kidola, Eveline Konje, Jim Todd, Farida Iddi Mkassy, Neema Mosha2026-06-28
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Bayesian Spatio-Temporal Bell Model for Count Data: Malaria Incidence in the Brazilian Legal Amazon

This study proposes and validates a Bayesian spatio-temporal Bell model for predicting malaria incidence in the Brazilian Legal Amazon, demonstrating its superior performance over traditional Poisson and Negative Binomial models in identifying high-risk microregions and timing for effective public health surveillance.

Moisés Augusto Farias Silva, Paulo Henrique Ferreira, Rosemeire Leovigildo Fiaccone, Madhuchhanda Bhattacharjee, Nixon J (…)2026-06-26
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Operationalizing Peer-Review Dynamics: A Quantitative Decision-Support System for Sustainable Editorial Governance

This paper introduces the Editorial Strategy Dashboard (ESD), a quantitative decision-support system that translates peer-review dynamics into auditable parameters, enabling editors to proactively balance submission volume, reviewer fatigue, and quality standards through evidence-based policy management rather than reactive intuition.

Jose A. Garcia, Rosa Rodriguez-Sanchez, J. Fdez-Valdivia2026-06-26
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Optimizing Irreversible Perturbations of the Unadjusted Langevin Algorithm

This paper presents a systematic framework for optimizing position-independent irreversible perturbations in the Unadjusted Langevin Algorithm by formulating a constrained optimization problem that balances mixing efficiency and discretization bias, resulting in an explicit optimal design that achieves faster convergence with controlled error.

Qianyu Zhu, Youssef Marzouk, Konstantinos Spiliopoulos, Benjamin Zhang2026-06-26
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An Empirical Study on Key Determinants in the Olympic Women's Basketball Final Based on Entropy-Weight WRSR Model — A Case Study of the 2024 USA vs. France Final

This study employs an objective Entropy-Weight WRSR model to analyze the 2024 Olympic Women's Basketball Final, identifying three-point shooting, foul control, steals, and blocks as key determinants and revealing that the French team's significant performance deviations in steals and blocks under pressure highlight systemic weaknesses in their defense and decision-making compared to the dominant USA team.

Zehui Zhang, Li Chen, Qilin Hu2026-06-25
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A Local Gaussian Process-Based Active Learning Method for Efficient Failure Probability Estimation

This paper proposes an efficient reliability analysis method that integrates local Gaussian processes, a novel adaptive learning function, and active subspaces to overcome the limitations of global optimization-based approaches in estimating failure probabilities for highly nonlinear, high-dimensional rare-event problems.

Junfeng Zhao, Luoyi Lu, Yuxuan Zheng, Hongdan Zheng, Pei Yin, Xiaofei Guan2026-06-25
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EPR-C3: A Deterministic Constraint-Aware Heuristic for High-Dimensional Subset Selection in Multiple Linear Regression

This paper introduces EPR-C3, a deterministic, constraint-aware heuristic that efficiently identifies high-quality, statistically admissible predictor subsets for high-dimensional multiple linear regression by combining structured neighborhood search with specific refinement steps, offering a computationally tractable alternative to exhaustive enumeration while outperforming existing selection methods.

Jackson J. Alcázar2026-06-25
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A Comparative Study of Methods for Handling Missing Data in Longitudinal Data with Implications for Causal Inference

This study utilizes Monte Carlo simulations and empirical validation to identify optimal combinations of missing data imputation and confounder control strategies for longitudinal causal inference, demonstrating that multiple imputation or random forest paired with doubly robust estimation yields the best performance for heterogeneous effects without unmeasured confounding.

Yemian Li, Yuhui Yang, Weiwei Hu, Zonghao Li, Fangyao Chen2026-06-25
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Generalized SEIR model and a new reproduction number reflecting the real epidemic dynamics

This paper proposes a generalized six-equation SEIR model incorporating re-infections, newborns, vaccinations, and an exposed compartment to address previous limitations, introduces a new reproduction number based on exposed population dynamics for epidemic control, and utilizes this framework to predict a resurgence of pertussis cases in England during mid-to-late 2027.

Igor Nesterruk2026-06-25