Daniel P Beavers, Yutong Li, James D Stamey, Stephanie Powers, Walter T Ambrosius
{"title":"Bayesian variable selection for logistic regression with a differentially misclassified binary covariate.","authors":"Daniel P Beavers, Yutong Li, James D Stamey, Stephanie Powers, Walter T Ambrosius","doi":"10.1080/03610918.2025.2496305","DOIUrl":"https://doi.org/10.1080/03610918.2025.2496305","url":null,"abstract":"<p><p>A Bayesian approach for variable selection is developed for use in models with a misclassified binary predictor variable. We define the main outcome model containing the latent predictor, the measurement model associated with the prevalence of the predictor, and the sensitivity and specificity models of the fallible classifier conditioned on the true value of the predictor. We use binary indicator variables to execute the Gibbs sampler-based variable selection process, and we identify the highest posterior probability model given the data. We demonstrate the performance of the procedure in several simulation studies, and we utilize the selection method to optimize model performance in two datasets.</p>","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12371521/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979315","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}
{"title":"Statistical methods for assessing treatment effects on ordinal outcomes using observational data.","authors":"Huirong Hu, Qi Zheng, Maiying Kong","doi":"10.1080/03610918.2025.2488945","DOIUrl":"https://doi.org/10.1080/03610918.2025.2488945","url":null,"abstract":"<p><p>In this article, we propose a marginal structural ordinal logistic regression model (MS-OLRM) to assess treatment effects on ordinal outcomes. Many statistical methods have been developed to estimate average treatment effect (ATE) when the outcome is continuous or binary. The methodology for assessing the effect of treatment for an ordinal outcome is less studied. To address this, we propose utilizing a superiority score as a measure of treatment effect, assessing whether the outcome under treatment is stochastically larger than the outcome under control. Our approach involves employing MS-OLRM in conjunction with Inverse Probability of Treatment Weighting (IPTW) to estimate the superiority score under treatment compared to the control. This methodology adjusts for confounding factors between treatment and outcome by utilizing IPTW, ensuring that all covariates are balanced among different treatment groups in the weighted sample. To assess the performance of the proposed method, we conduct extensive simulation studies. Finally, we apply the developed method to assess the treatment effects of medications and behavioral therapies on patients' recovery from alcohol use disorders using the Kentucky Medicaid 2012-2019 database.</p>","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12338247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979288","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}
{"title":"Automated Parameter Selection in Singular Spectrum Analysis for Time Series Analysis.","authors":"James J Yang, Anne Buu","doi":"10.1080/03610918.2025.2456575","DOIUrl":"https://doi.org/10.1080/03610918.2025.2456575","url":null,"abstract":"<p><p>In spite of wide applications of the singular spectrum analysis (SSA) method, understanding how SSA reconstructs time series and eliminates noise remains challenging due to its complex process. This study provided a novel geometric perspective to elucidate the underlying mechanism of SSA. To address the key issue of conventional SSA that requires a fixed window length and a given threshold for determining the number of groups, we proposed a sequential reconstruction approach that averages reconstructed series from various window lengths with a stopping rule based on a symmetric test. Three main advantages of the proposed method were demonstrated by the simulations and real data analysis of 7-day heart rate data from an e-cigarette user: 1) requiring no prior knowledge of the window length or group number; 2) yielding smaller values of root mean square error (RMSE) than the conventional SSA; and 3) revealing both local features and sudden changes related to events of interest. While conventional SSA excels in extracting stable signal structures, the proposed method is tailored for time series with varying structures such as heart rate data from smartwatches, and thus will have even wider applications.</p>","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352492/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979298","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}
{"title":"Adjusted curves for clustered survival and competing risks data.","authors":"Manoj Khanal, Soyoung Kim, Kwang Woo Ahn","doi":"10.1080/03610918.2023.2245583","DOIUrl":"10.1080/03610918.2023.2245583","url":null,"abstract":"<p><p>Observational studies with right-censored data often have clustered data due to matched pairs or a study center effect. In such data, there may be an imbalance in patient characteristics between treatment groups, where Kaplan-Meier curves or unadjusted cumulative incidence curves can be misleading and may not represent the average patient on a given treatment arm. Adjusted curves are desirable to appropriately display survival or cumulative incidence curves in this case. We propose methods for estimating the adjusted survival and cumulative incidence probabilities for clustered right-censored data. For the competing risks outcome, we allow both covariate-independent and covariate-dependent censoring. We develop an R package <b>adjSURVCI</b> to implement the proposed methods. It provides the estimates of adjusted survival and cumulative incidence probabilities along with their standard errors. Our simulation results show that the adjusted survival and cumulative incidence estimates of the proposed method are unbiased with approximate 95% coverage rates. We apply the proposed method to stem cell transplant data of leukemia patients.</p>","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":" 3","pages":"120-143"},"PeriodicalIF":0.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11708817/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72382911","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}
Gabriel Calvo, Carmen Armero, Luigi Spezia, Maria Grazia Pennino
{"title":"Bayes factors for longitudinal model assessment via power posteriors","authors":"Gabriel Calvo, Carmen Armero, Luigi Spezia, Maria Grazia Pennino","doi":"10.1080/03610918.2024.2399159","DOIUrl":"https://doi.org/10.1080/03610918.2024.2399159","url":null,"abstract":"Bayes factor, defined as the ratio of the marginal likelihood functions of two competing models, is the natural Bayesian procedure for model selection. Marginal likelihoods are usually computationa...","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"2 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259766","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}
R. Malekpour, T. Baghfalaki, M. Ganjali, A. Pourdarvish
{"title":"Joint modeling of mixed skewed longitudinal responses using convolution of normal and log-normal distributions: a Bayesian approach","authors":"R. Malekpour, T. Baghfalaki, M. Ganjali, A. Pourdarvish","doi":"10.1080/03610918.2024.2401437","DOIUrl":"https://doi.org/10.1080/03610918.2024.2401437","url":null,"abstract":"This paper investigates the joint modeling of mixed ordinal and continuous longitudinal responses using a random effects model and applying a conditional approach. For the ordinal responses, a late...","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"2 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259724","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}
Christina Hoffman, Jakini Auset Kauba, Julie C. Reidy, Thomas Weighill
{"title":"Statistical models of ballot truncation in ranked choice elections","authors":"Christina Hoffman, Jakini Auset Kauba, Julie C. Reidy, Thomas Weighill","doi":"10.1080/03610918.2024.2397032","DOIUrl":"https://doi.org/10.1080/03610918.2024.2397032","url":null,"abstract":"We introduce and study two new statistical models of ballot truncation – the process wherein voters neglect to rank every candidate during ranked choice voting (RCV). These models allow the incorpo...","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"188 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259727","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}
{"title":"Memory-type time-between-events charts using nonhomogeneous Poisson process","authors":"Sajid Ali","doi":"10.1080/03610918.2024.2401443","DOIUrl":"https://doi.org/10.1080/03610918.2024.2401443","url":null,"abstract":"The traditional time-between-events (TBE) control charts are developed in non-adaptive fashion assuming the Poisson process, where the TBE follows the exponential distribution. However, in many sit...","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"6 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259725","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}
Harpreet Singh, Seng Huat Ong, Choung Min Ng, Kurunathan Ratnavelu
{"title":"Poisson-stopped sum Lévy-type processes with application to stochastic modeling of hospital arrivals","authors":"Harpreet Singh, Seng Huat Ong, Choung Min Ng, Kurunathan Ratnavelu","doi":"10.1080/03610918.2024.2391883","DOIUrl":"https://doi.org/10.1080/03610918.2024.2391883","url":null,"abstract":"Patient arrivals at a hospital typically occur in clusters and the arrivals count data exhibits over-dispersion. To model these characteristics, the Lévy-type processes based on Poisson-stopped sum...","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"14 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259726","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}
Toh Kuan Wei, Nora Muda, Asyraf Nadia Mohd Yunus, Abdul Rahman Othman, Sonia Aïssa, Nor Aishah Ahad
{"title":"Approximation of the lognormal distribution as a solution to the sum of lognormal variates","authors":"Toh Kuan Wei, Nora Muda, Asyraf Nadia Mohd Yunus, Abdul Rahman Othman, Sonia Aïssa, Nor Aishah Ahad","doi":"10.1080/03610918.2024.2394571","DOIUrl":"https://doi.org/10.1080/03610918.2024.2394571","url":null,"abstract":"Lognormal distribution is widely used in modeling of variety fields such as fields of sciences and technology, human medicines, linguistics, social sciences and economics and others. In this resear...","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"13 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142207896","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}