Article
Mathematical & Computational Biology
Jonathan Yefenof, Yair Goldberg, Jennifer Wiler, Avishai Mandelbaum, Ya'acov Ritov
Summary: We study survival data that include uncensored, right-censored, and left-censored observations. A novel methodology for estimating the failure-time distribution using both semiparametric and nonparametric techniques is proposed. The estimators' performance is evaluated through simulated data. As a case study, we estimate the patience of patients at an emergency department waiting for treatment.
STATISTICS IN MEDICINE
(2022)
Article
Physics, Multidisciplinary
Luai Al-Labadi, Ayman Alzaatreh, Mark Asuncion
Summary: This paper presents a method for model checking in the presence of right-censored data, utilizing the relative belief ratio and the beta-Stacy process for computation. The proposed method compares the concentration of the posterior distribution to the concentration of the prior distribution, and is illustrated through various data analysis examples.
Article
Mathematical & Computational Biology
Alexander Seipp, Verena Uslar, Dirk Weyhe, Antje Timmer, Fabian Otto-Sobotka
Summary: Expectile regression offers a way to analyze the full conditional distribution of a response variable without making distributional assumptions, with computational simplicity and efficiency. The proposed extension with inverse probability weights can be used in right-censored data situations. The method provides easily interpreted tail expectations and can be applied to survival time analysis in medical research.
STATISTICS IN MEDICINE
(2021)
Article
Computer Science, Interdisciplinary Applications
Taehwa Choi, Arlene K. H. Kim, Sangbum Choi
Summary: Double censoring is common in biomedical research, especially in HIV/AIDS clinical trials. This article proposes a method for the accelerated failure time model under double random censoring and establishes asymptotic properties. Simulation studies show that the method performs well under various censoring schemes.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2021)
Article
Statistics & Probability
Asamh Saleh M. Al Luhayb, Frank P. A. Coolen, Tahani Coolen-Maturi
Summary: This paper introduces a smoothed bootstrap method based on the right-censoring-A((n)) assumption proposed by Coolen and Yan, which is a generalization of Hill's A((n)) assumption for right-censored data. The performance of the smoothed bootstrap method is compared to Efron's method for right-censored data through simulations. The results show that the smoothed bootstrap method outperforms Efron's method, especially for small data sets. The method is also applied to survival function inference and compared to a smoothed Kaplan-Meier bootstrap method through simulations.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2023)
Article
Statistics & Probability
Shanghong Xie, Thaddeus Tarpey, Eva Petkova, R. Todd Ogden
Summary: This article proposes an approach to improve the accuracy of individualized treatment rules (ITRs) by using multiple kernel functions to describe the similarity of features. The method takes into account the heterogeneity of each data domain and combines data from multiple domains optimally. The approach can estimate optimal ITRs and identify the most important domains for determining ITRs.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2022)
Article
Mathematics, Interdisciplinary Applications
Qiqing Yu
Summary: Parametric inferences were conducted on a breast cancer data set censored with the uniform distribution U(a, b). It was found that the MLE for a has a closed form solution, while the MLE for b has a closed form solution in some sense. A diagnostic plotting method and test for U(a, b) were proposed, along with investigation into the asymptotic properties of the MLE. Results showed that the breast cancer data set fits both U(a, b) and Exp(theta), with U(a, b) leading to more useful and reasonable inferences compared to other methods.
LIFETIME DATA ANALYSIS
(2021)
Article
Statistics & Probability
Marija Cuparic
Summary: This paper explores a class of empirical processes associated with U-statistics, focusing on right-censored data that is reweighted using the inverse of the censoring random variable's survival function. Asymptotic properties of these U-empirical processes are derived and applied to two different goodness-of-fit tests.
Article
Statistics & Probability
Hailin Feng, Qianqian Luo
Summary: Quantile regression is highly flexible in describing the relationship between covariates and response variables. This paper introduces a new weighted quantile regression method for nonlinear models with randomly censored responses, which can handle more complex quantile regression models within the range of (0, 1). The consistency, asymptotic normality, and finite sample performance of the proposed estimator are also examined in this study.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2021)
Article
Statistics & Probability
Sangbum Choi, Xuelin Huang
Summary: This article examines nonparametric maximum likelihood estimation of semiparametric transformation models for doubly-censored data in medical studies, such as HIV/AIDS clinical trials. The estimator is consistent and asymptotically normal, with statistical inferences conveniently made from the inverse of the observed information matrix. Simulation studies show that the NPMLE performs well even under heavy censoring and outperforms methods based on estimating functions in terms of efficiency.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2021)
Article
Health Care Sciences & Services
Yizhe Xu, Tom H. Greene, Adam P. Bress, Brandon K. Bellows, Yue Zhang, Zugui Zhang, Paul Kolm, William S. Weintraub, Andrew S. Moran, Jincheng Shen
Summary: This study focuses on the importance of evidence from observational studies for healthcare policy making and proposes a statistical tool for learning cost-effective individualized treatment rules. The tool considers subject-level heterogeneity and utilizes the concept of net-monetary-benefit to assess the trade-off between health benefits and related costs.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2022)
Article
Statistics & Probability
Grzegorz Wylupek
Summary: The paper introduces a novel approach to address a classical two-sample problem with right-censored data and develops an efficient procedure for verifying equality of two survival curves. It generalizes the log-rank test, with the new test statistic having an asymptotic Chi-square distribution with one degree of freedom under the null hypothesis, while being consistent for a wide range of alternatives. Additionally, permutation approach is employed for inference to control the actual Type I error rate when sample sizes are finite, showing that the new test procedure outperforms classical solutions and recent developments in the field through extensive simulation studies.
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
(2021)
Article
Statistics & Probability
Qiqing Yu
Summary: This paper studies the generalised maximum likelihood estimator (GMLE) of a survival function based on truncated interval-censored (TIC) data, and resolves issues regarding the formulation of innermost intervals and the consistency of the GMLE.
JOURNAL OF NONPARAMETRIC STATISTICS
(2023)
Article
Statistics & Probability
Vincent Margot, Jean-Patrick Baudry, Frederic Guilloux, Olivier Wintenberger
Summary: The procedure introduces an estimator for the regression function based on a data-dependent quasi-covering, ensuring consistency and interpretability. The proof of consistency relies on controlling the convergence rate of empirical estimation of conditional expectations, avoiding common conditions found in literature for data-dependent partitioning estimators.
ELECTRONIC JOURNAL OF STATISTICS
(2021)
Article
Statistics & Probability
Shunping Zheng, Fei Zhang, Chunhua Wang, Xuejun Wang
Summary: In this paper, we investigate the weak convergence and convergence rate in the weak law of large numbers for a specific class of random variables that satisfy the Rosenthal type inequality. We provide necessary and sufficient conditions for the convergence rates in the weak law of large numbers under certain mild conditions. Furthermore, we apply our main results to simple linear errors-in-variables regression models and nonparametric regression models based on a class of random errors. We also conduct numerical simulations to assess the finite sample performance of the theoretical results.
Article
Statistics & Probability
Ruoqing Zhu, Donglin Zeng, Michael R. Kosorok
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2015)
Article
Biology
Ruoqing Zhu, Ying-Qi Zhao, Guanhua Chen, Shuangge Ma, Hongyu Zhao
Article
Mathematical & Computational Biology
Ruoqing Zhu, Qing Zhao, Hongyu Zhao, Shuangge Ma
Article
Health Policy & Services
Elizabeth M. La, Kristen Hassmiller Lich, Rebecca Wells, Alan R. Ellis, Marvin S. Swartz, Ruoqing Zhu, Joseph P. Morrissey
PSYCHIATRIC SERVICES
(2016)
Article
Biochemical Research Methods
U. Hassan, R. Zhu, R. Bashir
Article
Genetics & Heredity
Ruoqing Zhu, Hongyu Zhao, Shuangge Ma
GENETIC EPIDEMIOLOGY
(2014)
Article
Statistics & Probability
Lixing Zhu, Ruoqing Zhu, Song Song
JOURNAL OF MULTIVARIATE ANALYSIS
(2008)
Article
Statistics & Probability
Ruoqing Zhu, Michael R. Kosorok
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2012)
Article
Multidisciplinary Sciences
Ishan Taneja, Bobby Reddy, Gregory Damhorst, Sihai Dave Zhao, Umer Hassan, Zachary Price, Tor Jensen, Tanmay Ghonge, Manish Patel, Samuel Wachspress, Jake Winter, Michael Rappleye, Gillian Smith, Ryan Healey, Muhammad Ajmal, Muhammad Khan, Jay Patel, Harsh Rawal, Raiya Sarwar, Sumeet Soni, Anwaruddin Benjamin Davis, James Kumar, Karen White, Rashid Bashir, Ruoqing Zhu
SCIENTIFIC REPORTS
(2017)
Article
Environmental Sciences
Christian A. Maino Vieytes, Ruoqing Zhu, Francesca Gany, Amirah Burton-Obanla, Anna E. Arthur
Summary: This study reveals the impact of food insecurity on the dietary patterns of cancer survivors in the United States, emphasizing the importance of screening and monitoring food insecurity in this vulnerable population.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Health Policy & Services
Elizabeth Holdsworth La, Ruoqing Zhu, Kristen Hassmiller Lich, Alan R. Ellis, Marvin S. Swartz, Michael R. Kosorok, Joseph P. Morrissey
ADMINISTRATION AND POLICY IN MENTAL HEALTH AND MENTAL HEALTH SERVICES RESEARCH
(2015)