Article
Mathematical & Computational Biology
Peter Z. Schochet
Summary: In clustered randomized controlled trials, sample recruitment occurring after cluster randomization can lead to recruitment bias. This article presents a potential outcomes framework that yields a causal estimand related to individuals always recruited into the research conditions. A consistent inverse probability weighting estimator is developed using data on recruits only, and a generalized estimating equations approach is used to obtain robust clustered standard error estimators that account for estimation error in the weighting. A simple data collection strategy is discussed to improve the predictive accuracy of the logit propensity score models.
STATISTICS IN MEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Youjun Huang, Jianxin Pan
Summary: Modeling longitudinal binary data with constraints on the correlation coefficients is achieved by a novel joint GEE method, which shows good performance in simulation studies even under misspecified covariance structures. The proposed method allows for simultaneous modeling of mean and within-subject correlation coefficients, taking into account the upper bound of the correlation coefficients.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2021)
Article
Mathematical & Computational Biology
Seonjin Kim, Hyunkeun Ryan Cho, Mi-Ok Kim
Summary: The study proposes a nonparametric bivariate varying coefficient generalized linear model to predict future mean response trajectories by utilizing a combination of kernel and spline methods. The research also develops a new bootstrap approach for statistical inference and applies the methodology to the Framingham Heart Study.
STATISTICS IN MEDICINE
(2021)
Article
Mathematical & Computational Biology
Meng Liu, Yang Zhao
Summary: In this study, new WGEEs for missing at random data were proposed, with a unified approach to improve estimation efficiency. The proposed method showed consistent and more efficient results in simulation studies with both continuous response and binary response data.
STATISTICS IN MEDICINE
(2022)
Article
Education & Educational Research
Francis L. Huang
Summary: This article introduces the generalized estimating equations (GEEs) approach for analyzing clustered data, which is less commonly used in the education field. Through worked examples with continuous and binary outcomes, comparisons are made between GEEs, multilevel models, and ordinary least squares to highlight similarities and differences between the methods. Detailed walkthroughs are provided using both R and SPSS Version 26.
JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS
(2022)
Article
Statistics & Probability
Tun Lee Ng, Michael A. Newton
Summary: This article establishes the statistical properties of random-weighting methods in LASSO regression under different regularization parameters and suitable regularity conditions. By assigning random weights to terms in the objective function and optimizing them, we obtain a set of random-weighting estimators. The study shows that existing methods have conditional model selection consistency and conditional asymptotic normality at different growth rates. Moreover, an extension to these methods is proposed, demonstrating conditional sparse normality and consistency in a growing-dimension setting. The effectiveness of the proposed methodology is illustrated using synthetic and benchmark datasets, and its relationship to approximate nonparametric Bayesian analysis and perturbation bootstrap methods is discussed.
ELECTRONIC JOURNAL OF STATISTICS
(2022)
Article
Biochemical Research Methods
Han Sun, Xiaoyun Huang, Ban Huo, Yuting Tan, Tingting He, Xingpeng Jiang
Summary: The study developed a novel method called aGEEMIHC to detect sparse microbial association signals in longitudinal microbiome data using generalized estimating equations. Simulation experiments showed that aGEEMiHC achieved superior statistical power and stability for different types of host phenotypes.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Mathematical & Computational Biology
Youjun Huang, Jianxin Pan
Summary: The paper proposes a PJGEE method based on SCAD and LASSO for modeling the mean and correlations of longitudinal binary data, along with variable selection. Simulation studies show that the method outperforms existing PGEE methods in terms of variable selection consistency and parameter estimation accuracy. Analysis on a real data set further confirms the effectiveness of the method.
BIOMETRICAL JOURNAL
(2022)
Article
Computer Science, Interdisciplinary Applications
Renwen Luo, Jianxin Pan
Summary: Joint modelling of mean-covariance structure is important in clustered data analysis. Existing methods have limitations in assuming natural order in responses and modeling transformed parameters. The proposed data-driven method is flexible, interpretable, and works on original correlation coefficients and variances without the need for natural order.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2022)
Article
Mathematics, Applied
H. M. Barakat, Magdy E. El-Adll, M. E. Sobh
Summary: This paper investigates the bootstrap properties of in-generalized order statistics (m-GOSs) with variable rank, focusing on the inconsistency, weak consistency, and strong consistency of bootstrapping central and intermediate m-GOSs. It provides sufficient conditions for the weak and strong consistencies based on normalizing constant estimators, and conducts a simulation study to determine the optimal bootstrap re-sample size for best fitting of the bootstrapping distribution.
Article
Statistics & Probability
Laura Dumitrescu, Ioana Schiopu-Kratina
Summary: This study examines the properties of estimators obtained from estimating functions, primarily applied to exponential family distributions in evolutionary clustered data. Estimating equations accommodating different dependencies are constructed within a quasi-likelihood approach, extending results of linear and generalized linear models, and characterizing asymptotically optimal estimating functions.
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
(2021)
Article
Mathematical & Computational Biology
Ruofan Bie, Sebastien Haneuse, Nathan Huey, Jonathan Schildcrout, Glen McGee
Summary: In settings with correlated data, analysts often choose between fitting conditional and marginal models based on scientific grounds. In small-sample settings, GEE and MMMs exhibit similar performance but MMMs may be more sensitive to misspecification of the correlation structure.
STATISTICS IN MEDICINE
(2021)
Article
Economics
Yi He, Liang Peng, Dabao Zhang, Zifeng Zhao
Summary: In this study, we compute the value-at-risk of financial losses by fitting a generalized Pareto distribution, and find that the asymptotic variance of the maximum likelihood estimation depends on the choice of threshold. We propose a random weighted bootstrap method for interval estimation of VaR, whose critical values are computed based on the empirical distribution of the differences between bootstrapped estimators and the maximum likelihood estimator. Our asymptotic results show that the confidence intervals derived cover the true VaR well in insurance and finance, as demonstrated through finite sample studies using simulation and real data.
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
(2022)
Article
Health Care Sciences & Services
Angelika Geroldinger, Rok Blagus, Helen Ogden, Georg Heinze
Summary: In binary logistic regression, separable data refers to the existence of a linear combination of explanatory variables that perfectly predicts the outcome. Firth's logistic regression (FL) is a popular solution to obtain finite estimates in such cases. When analyzing clustered data, like in clinical research, using generalized estimating equations (GEE), convergence becomes more complicated. This article investigates extensions of FL to GEE and compares their convergence behavior and performance using simulated and real data.
BMC MEDICAL RESEARCH METHODOLOGY
(2022)
Article
Economics
Yanxi Hou, Seul Ki Kang, Chia Chun Lo, Liang Peng
Summary: This paper proposes an efficient three-step procedure to deal with the semicontinuous property of insurance claim data and forecast extreme risk. The procedure combines logistic regression, quantile regression, and generalized Pareto distribution fitting to achieve accurate risk forecasting. The uncertainty of the derived risk forecast is quantified using a random weighted bootstrap method.
INSURANCE MATHEMATICS & ECONOMICS
(2022)
Article
Automation & Control Systems
Dong Mei, Zhu-Qing Yu
ASSEMBLY AUTOMATION
(2020)
Article
Construction & Building Technology
Jinfeng Sun, Liang Tian, Zhuqing Yu, Yu Zhang, Chengdong Li, Guihua Hou, Xiaodong Shen
CONSTRUCTION AND BUILDING MATERIALS
(2020)
Article
Construction & Building Technology
Chenxin Ni, Qingyong Wu, Zhuqing Yu, Xiaodong Shen
Summary: The fineness of densified silica fume (DSF) significantly affects the hydration of cement, with larger agglomerations delaying the hydration process while finer particles contribute to improved compressive strength of cement mortar.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Review
Green & Sustainable Science & Technology
Qingyong Wu, Qingzong Xue, Zhuqing Yu
Summary: Super sulfate cement (SSC) is an ideal green building material made from industrial solid wastes, with good resistance to sulfate attack but poor resistance to carbonation, and its drawbacks include slow hydration hardening and low early strength. Despite the limitations, with increasing environmental requirements, research and use of SSC in concrete continue to grow in this century.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Automation & Control Systems
Dong Mei, Zhu-Qing Yu
Summary: This study develops a disturbance rejection control scheme based on the active disturbance rejection control (ADRC) inverse estimation algorithm to improve the anti-interference capability of an airborne radar stabilized platform. By using an inverse ESO and feedback control, the algorithm shows better disturbance rejection performance, especially in complex air conditions with continuous interference.
ASSEMBLY AUTOMATION
(2021)
Article
Gastroenterology & Hepatology
William J. Sandborn, James D. Lewis, Julian Panes, Edward Loftus, Geert D'Haens, Zhuqing Yu, Bidan Huang, Ana P. Lacerda, Aileen L. Pangan, Brian G. Feagan
Summary: This study examined the association between patient-reported general well-being and symptoms of diarrhea and abdominal pain in patients with moderate to severe Crohn's disease. The findings suggest that improvements in patient-reported general well-being are related to clinical remission/response, supporting the endpoint definitions used in clinical studies of Crohn's disease.
JOURNAL OF CROHNS & COLITIS
(2022)
Article
Statistics & Probability
Shengchun Kong, Zhuqing Yu, Xianyang Zhang, Guang Cheng
Summary: This paper proposes a desparsified Lasso estimator based on the log partial likelihood function for high-dimensional inference in potentially misspecified Cox proportional hazard models. The estimator is shown to converge to a pseudo-true parameter vector and allows inference of the sparsity of the true parameter. Each component of the estimator is proven to be asymptotically normal, with a variance that can be consistently estimated even under model misspecifications, leading to valid statistical inference procedures in some cases.
SCANDINAVIAN JOURNAL OF STATISTICS
(2021)
Article
Construction & Building Technology
Qingzong Xue, Chenxin Ni, Qingyong Wu, Zhuqing Yu, Xiaodong Shen
Summary: The study showed that nano-CSH can accelerate the hydration process of cement-based materials, especially in samples containing GGBFS. The presence of nano-CSH can also speed up the secondary hydration reaction of mineral admixtures.
JOURNAL OF SUSTAINABLE CEMENT-BASED MATERIALS
(2022)
Article
Thermodynamics
Jian Ma, Xiaomin Liu, Zhuqing Yu, Hu Shi, Qingyong Wu, Xiaodong Shen
Summary: This paper thoroughly investigates the effects of limestone powder on the hydration of Portland cement and the formation and transformation mechanism of calcium carboaluminate phases. The results show that the addition of limestone powder delays the formation of hemicarboaluminate and reduces chemical shrinkage.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2022)
Review
Construction & Building Technology
Jian Ma, Ting Wang, Haonan Wang, Zhuqing Yu, Xiaodong Shen
Summary: This paper provides a comprehensive review of the application of calcareous fillers in alkali activated cement, discussing their effects on cement properties and emphasizing crucial factors. The proposed action mechanism of calcareous fillers in cement is also summarized.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Chemistry, Physical
Jian Ma, Ting Wang, Hu Shi, Zhuqing Yu, Xiaodong Shen
Summary: This study investigates the effects of limestone powder and gypsum on the early hydration of ye'elimite. The results show that adding limestone powder has a comparable hydration heat evolution to systems without limestone powder, and increasing the dosage of limestone powder shortens the level off time of chemical shrinkage. The thermodynamic modelling results further support the experimental findings.
Review
Construction & Building Technology
Jian Ma, Haonan Wang, Zhuqing Yu, Hu Shi, Qingyong Wu, Xiaodong Shen
Summary: This paper reviews the research progress on the performance and relevant mechanisms of calcium sulphoaluminate (CSA) cement in chloride environment, emphasizing the crucial factors influencing its resistance to chloride attack and recommending future research directions.
JOURNAL OF SUSTAINABLE CEMENT-BASED MATERIALS
(2023)
Article
Construction & Building Technology
Xiaomin Liu, Yu Long, Qingyong Wu, Zhuqing Yu, Xiaodong Shen
Summary: Red mud is a solid waste produced during the production of alumina. Its long-term storage can lead to land occupation and serious pollution to soil, air, and water. Alkali activated cementitious material (AACM) provides a new approach for the efficient utilization of red mud.
MATERIALS AND STRUCTURES
(2023)
Article
Chemistry, Physical
Jian Wu, Hai Zheng, Mingliang Tang, Zhuqing Yu, Zhigang Pan
Summary: In this study, SiC nanoparticles were used to enhance the mechanical properties of alumina ceramics. The rheological properties of the slurry were characterized, and the sintering shrinkage and strength of the composite ceramics were tested. The addition of 8 wt% SiC nanoparticles increased the flexural strength and fracture toughness of the ceramics by 42% and 41% respectively.
Article
Thermodynamics
Renwang Nie, Qingyong Wu, Zhuqing Yu, Aiguo Wang, Xiaodong Shen
Summary: This study investigated a new method of utilizing coral waste in concrete, and found that GGBFS can enhance the hydration of CP in cement, improving the mechanical properties of the concrete structures.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2022)
Article
Statistics & Probability
Tsung- Lin, Wan-Lun Wang
Summary: This paper derives explicit expressions for the moments of truncated multivariate normal/independent distributions with supports confined within a hyper-rectangle. A Monte Carlo experiment is conducted to validate the proposed formulae for five selected members of the distributions.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Statistics & Probability
Tao Qiu, Qintong Zhang, Yuanyuan Fang, Wangli Xu
Summary: This article introduces a method for testing the homogeneity of two random vectors. The method involves selecting two subspaces and projecting them onto one-dimensional spaces, using the Cramer-von Mises distance to construct the test statistic. The performance is enhanced by repeating this procedure and the effectiveness is demonstrated through numerical simulations.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Statistics & Probability
Alfredo Alegria, Xavier Emery
Summary: This study contributes to covariance modeling by proposing new parametric families of isotropic matrix-valued functions that exhibit non-monotonic behaviors, such as hole effects and cross-dimples. The benefit of these models is demonstrated on a bivariate dataset of airborne particulate matter concentrations.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Statistics & Probability
Kento Egashira, Kazuyoshi Yata, Makoto Aoshima
Summary: This study investigates the asymptotic properties of hierarchical clustering in different settings, including high-dimensional, low-sample-size scenarios. The results show that hierarchical clustering exhibits good asymptotic properties under practical settings for high-dimensional data. The study also extends the analysis to consider scenarios where both the dimension and sample size approach infinity, and generalizes the concept of populations in multiclass HDLSS settings.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Statistics & Probability
Marlene Baumeister, Marc Ditzhaus, Markus Pauly
Summary: This paper introduces a more robust multivariate analysis method by using general quantiles, particularly the median, instead of the traditional mean, and applies and validates this method on various factorial designs. The effectiveness of this method is demonstrated through theoretical and simulation studies on small and moderate sample sizes.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Statistics & Probability
Chuancun Yin, Narayanaswamy Balakrishnan
Summary: The family of multivariate skew-normal distributions has interesting properties, which also hold for a general class of skew-elliptical distributions.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
Article
Statistics & Probability
Gaspard Bernard, Thomas Verdebout
Summary: In this paper, we address the problem of testing the relationship between the eigenvalues of a scatter matrix in an elliptical distribution. Using the Le Cam asymptotic theory, we show that the non-specification of nuisance parameters has an asymptotic cost for testing the relationship. We also propose a distribution-free signed-rank test for this problem.
JOURNAL OF MULTIVARIATE ANALYSIS
(2024)
