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Communications in Statistics - Theory and Methods最新文献

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Parameter-expanded data augmentation for analyzing multinomial probit models. 分析多项概率模型的参数扩展数据扩充。
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2025-09-11 DOI: 10.1080/03610926.2025.2559116
Xiao Zhang
{"title":"Parameter-expanded data augmentation for analyzing multinomial probit models.","authors":"Xiao Zhang","doi":"10.1080/03610926.2025.2559116","DOIUrl":"10.1080/03610926.2025.2559116","url":null,"abstract":"<p><p>The multinomial probit model has been a prominent tool to analyze nominal categorical data, but the computational complexity of maximum likelihood functions presents challenges in the usage of this model. Furthermore, the model identification is extremely tenuous and usually necessitates the covariance matrix of the latent multivariate normal variables to be a restricted covariance matrix, which brings a rigorous task for both likelihood-based estimation and Markov chain Monte Carlo (MCMC) sampling. We tackle this issue by constructing a non-identifiable model and developing parameter-expanded data augmentation. Our proposed methods circumvent sampling a restricted covariance matrix commonly implemented by a painstaking Metropolis-Hastings (MH) algorithm and enable to sample a covariance matrix without restriction through a Gibbs sampler. Therefore, our proposed methods advance the convergence and mixing of the MCMC components considerably. We investigate our proposed methods along with the method based on the identifiable model through simulation studies and further illustrate their performance by an application to consumer choice on liquid laundry detergents data.</p>","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483000/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Regression Modeling of Cumulative Incidence Function for Left-Truncated Right-Censored Competing Risks Data: A Modified Pseudo-observation Approach. 左截右删竞争风险数据累积关联函数的回归建模：一种改进的伪观测方法。
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2025-02-11 DOI: 10.1080/03610926.2025.2458183
Rong Rong, Jing Ning, Hong Zhu
{"title":"Regression Modeling of Cumulative Incidence Function for Left-Truncated Right-Censored Competing Risks Data: A Modified Pseudo-observation Approach.","authors":"Rong Rong, Jing Ning, Hong Zhu","doi":"10.1080/03610926.2025.2458183","DOIUrl":"10.1080/03610926.2025.2458183","url":null,"abstract":"<p><p>Statistical methods have been developed for regression modeling of the cumulative incidence function (CIF) given left-truncated right-censored competing risks data. Nevertheless, existing methods typically involve complicated weighted estimating equations or nonparametric conditional likelihood function and often require a restrictive assumption that censoring and/or truncation times are independent of failure time. The pseudo-observation (PO) approach has been used in regression modeling of CIF for right-censored competing risks data under covariate-independent censoring or covariate-dependent censoring. We extend this approach to left-truncated right-censored competing risks data and propose to directly model the CIF based on POs, under general truncation and censoring mechanisms. We adjust for covariate-dependent truncation and/or covariate-dependent censoring by incorporating covariate-adjusted weights into the inverse probability weighted (IPW) estimator of the CIF. We derive large sample properties of the proposed estimators under reasonable model assumptions and regularity conditions and assess their finite sample performances by simulation studies under various scenarios. We apply the proposed method to a cohort study on pregnancy exposed to coumarin derivatives.</p>","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12396585/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144945685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sample size estimation for the ratio of count outcomes in a cluster randomized trial using GEE. 使用GEE的聚类随机试验中计数结果比率的样本量估计。
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2025-01-01 Epub Date: 2025-01-05 DOI: 10.1080/03610926.2024.2439998
Jijia Wang, Song Zhang, Chul Ahn
{"title":"Sample size estimation for the ratio of count outcomes in a cluster randomized trial using GEE.","authors":"Jijia Wang, Song Zhang, Chul Ahn","doi":"10.1080/03610926.2024.2439998","DOIUrl":"10.1080/03610926.2024.2439998","url":null,"abstract":"<p><p>Count outcomes often occur in cluster randomized trials. Particularly in the context of epidemiology, the ratio of incidence rates has been used to assess the effectiveness of an intervention. In practice, cluster sizes typically vary across clusters, and sample size estimation based on a constant cluster size assumption may lead to underpowered studies. To address this issue, we propose a sample size method based on the generalized estimating equation (GEE) approach to test the ratio of two incidence rates. A closed-form sample size formula is presented, which is flexible to account for unbalanced randomization and randomly varying cluster sizes. Simulations were performed to assess its performance. In cluster randomized trials of vaccine efficacy, the ratio of disease incidence rates has been frequently used to demonstrate that the vaccine reduces the occurrence of a disease compared to placebo or active control. An application example to the design of a vaccine efficacy cluster randomized trial is presented.</p>","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":"54 17","pages":"5470-5479"},"PeriodicalIF":0.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145029093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identifiability and convergence behavior for Markov chain Monte Carlo using multivariate probit models. 马尔可夫链蒙特卡罗多变量概率模型的可辨识性和收敛性。
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2025-01-01 Epub Date: 2024-11-09 DOI: 10.1080/03610926.2024.2425738
Xiao Zhang
{"title":"Identifiability and convergence behavior for Markov chain Monte Carlo using multivariate probit models.","authors":"Xiao Zhang","doi":"10.1080/03610926.2024.2425738","DOIUrl":"https://doi.org/10.1080/03610926.2024.2425738","url":null,"abstract":"<p><p>Multivariate probit models have been popularly utilized to analysis multivariate ordinal data. However, the identifiable multivariate probit models entail the covariance matrix for the underlying multivariate normal variables to be a correlation matrix, which brings a rigorous task to conduct efficient statistical analysis. Parameter expansion to make the identifiable model to be non-identifiable has been inevitably explored. However, the effect of the expanded parameters on the convergence of Markov chain Monte Carlo (MCMC) is seldomly investigated; in addition, the comparison of MCMC developed based on the identifiable model and that based on the non-identifiable model is hardly ever explored, especially for data with large sample sizes. In this paper, we conduct a thorough investigation to illustrate the effect of the expanded parameters on the convergence of MCMC and compare the behavior of MCMC between the identifiable and non-identifiable models. Our investigation provides a practical guide regarding the construction of non-identifiable models and development of corresponding MCMC sampling methods. We conduct our investigation using simulation studies and present an application using data from the Russia Longitudinal Monitoring Survey-Higher School of Economics (RLMS-HSE) study.</p>","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":"54 14","pages":"4600-4615"},"PeriodicalIF":0.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12366764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144945723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A multiple imputation method using population information 利用人口信息的多重估算方法
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2024-09-13 DOI: 10.1080/03610926.2024.2395880
Tadayoshi Fushiki
{"title":"A multiple imputation method using population information","authors":"Tadayoshi Fushiki","doi":"10.1080/03610926.2024.2395880","DOIUrl":"https://doi.org/10.1080/03610926.2024.2395880","url":null,"abstract":"Multiple imputation (MI) is effectively used to deal with missing data when the missing mechanism is missing at random. However, MI may not be effective when the missing mechanism is not missing at...","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":"26 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel method for approximating the distribution of chi-squared-type mixtures 逼近奇平方型混合物分布的新方法
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2024-09-11 DOI: 10.1080/03610926.2024.2393703
Zhengbang Li, Yujie Jiao, Pan Fu, Jiayan Zhu
{"title":"A novel method for approximating the distribution of chi-squared-type mixtures","authors":"Zhengbang Li, Yujie Jiao, Pan Fu, Jiayan Zhu","doi":"10.1080/03610926.2024.2393703","DOIUrl":"https://doi.org/10.1080/03610926.2024.2393703","url":null,"abstract":"In order to approximate the distribution of chi-squared-type mixtures, Zhang (2005) proposed to use a chi-squared-type random variable of the form α1χd12+β1, where the unknown parameters α1, β1, an...","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":"48 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Functional quantile regression with missing data in reproducing kernel Hilbert space 再现核希尔伯特空间中缺失数据的函数量子回归
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2024-09-03 DOI: 10.1080/03610926.2024.2392857
Xiao-Ge Yu, Han-Ying Liang
{"title":"Functional quantile regression with missing data in reproducing kernel Hilbert space","authors":"Xiao-Ge Yu, Han-Ying Liang","doi":"10.1080/03610926.2024.2392857","DOIUrl":"https://doi.org/10.1080/03610926.2024.2392857","url":null,"abstract":"We, in this article, focus on functional partially linear quantile regression, where the observations are missing at random, which allows the response or covariates or response and covariates simul...","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":"32 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Stochastic comparisons of second largest order statistics with dependent heterogeneous random variables 具有依存异质随机变量的第二大阶统计的随机比较
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2024-09-03 DOI: 10.1080/03610926.2024.2392858
Man-Yuan Guo, Jiandong Zhang, Rongfang Yan
{"title":"Stochastic comparisons of second largest order statistics with dependent heterogeneous random variables","authors":"Man-Yuan Guo, Jiandong Zhang, Rongfang Yan","doi":"10.1080/03610926.2024.2392858","DOIUrl":"https://doi.org/10.1080/03610926.2024.2392858","url":null,"abstract":"In the context of actuarial science, the second largest claim amount is crucial to insurance analysis since they provide useful information for determining annual premium. In this article, we provi...","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":"27 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Testing the ratio of two Poisson means based on an inferential model 根据推理模型测试两个泊松均值之比
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2024-09-02 DOI: 10.1080/03610926.2024.2395882
Yanting Chen, Xionghui Ou, Kai Wan, Chunxin Wu, Shaofang Kong, Chao Chen
{"title":"Testing the ratio of two Poisson means based on an inferential model","authors":"Yanting Chen, Xionghui Ou, Kai Wan, Chunxin Wu, Shaofang Kong, Chao Chen","doi":"10.1080/03610926.2024.2395882","DOIUrl":"https://doi.org/10.1080/03610926.2024.2395882","url":null,"abstract":"The ratio of two Poisson means is commonly used in biological, epidemiological, and medical. In this article, we consider the problem of testing the ratio of two Poisson means and propose a valid a...","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":"9 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimal maintenance policies for a k-out-of-n system with replacement bias costs 具有替换偏差成本的 k-out-of-n 系统的最佳维护政策
IF 0.8 4区 数学
Communications in Statistics - Theory and Methods Pub Date : 2024-08-31 DOI: 10.1080/03610926.2024.2397066
Chin-Chih Chang, Yen-Luan Chen
{"title":"Optimal maintenance policies for a k-out-of-n system with replacement bias costs","authors":"Chin-Chih Chang, Yen-Luan Chen","doi":"10.1080/03610926.2024.2397066","DOIUrl":"https://doi.org/10.1080/03610926.2024.2397066","url":null,"abstract":"In this paper, the issue of determining an optimal age replacement is explored by incorporating minimal repair, preventive replacement, and corrective replacement into a k-out-of-n system subject t...","PeriodicalId":10531,"journal":{"name":"Communications in Statistics - Theory and Methods","volume":"26 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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