Biostatistics最新文献_第3页

Bayesian estimation of covariate assisted principal regression for brain functional connectivity. 针对大脑功能连接性的协变量辅助主回归贝叶斯估计。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae023

Hyung G Park

引用次数: 0

Semiparametric mixture regression for asynchronous longitudinal data using multivariate functional principal component analysis. 基于多元泛函主成分分析的异步纵向数据半参数混合回归。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxaf008

Ruihan Lu, Yehua Li, Weixin Yao

{"title":"Semiparametric mixture regression for asynchronous longitudinal data using multivariate functional principal component analysis.","authors":"Ruihan Lu, Yehua Li, Weixin Yao","doi":"10.1093/biostatistics/kxaf008","DOIUrl":"10.1093/biostatistics/kxaf008","url":null,"abstract":"The transitional phase of menopause induces significant hormonal fluctuations, exerting a profound influence on the long-term well-being of women. In an extensive longitudinal investigation of women's health during mid-life and beyond, known as the Study of Women's Health Across the Nation (SWAN), hormonal biomarkers are repeatedly assessed, following an asynchronous schedule compared to other error-prone covariates, such as physical and cardiovascular measurements. We conduct a subgroup analysis of the SWAN data employing a semiparametric mixture regression model, which allows us to explore how the relationship between hormonal responses and other time-varying or time-invariant covariates varies across subgroups. To address the challenges posed by asynchronous scheduling and measurement errors, we model the time-varying covariate trajectories as functional data with reduced-rank Karhunen-Loéve expansions, where splines are employed to capture the mean and eigenfunctions. Treating the latent subgroup membership and the functional principal component (FPC) scores as missing data, we propose an Expectation-Maximization algorithm to effectively fit the joint model, combining the mixture regression for the hormonal response and the FPC model for the asynchronous, time-varying covariates. In addition, we explore data-driven methods to determine the optimal number of subgroups within the population. Through our comprehensive analysis of the SWAN data, we unveil a crucial subgroup structure within the aging female population, shedding light on important distinctions and patterns among women undergoing menopause.","PeriodicalId":55357,"journal":{"name":"Biostatistics","volume":"26 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11929387/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Testing for a difference in means of a single feature after clustering. 聚类后对单个特征的均值差异进行测试。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae046

Yiqun T Chen, Lucy L Gao

引用次数: 0

Correction to: Scalable kernel balancing weights in a nationwide observational study of hospital profit status and heart attack outcomes. 修正：在一项全国性的医院盈利状况和心脏病发作结果的观察性研究中，可扩展的核平衡权值。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae050

引用次数: 0

Recurrent events modeling based on a reflected Brownian motion with application to hypoglycemia. 基于反射布朗运动的反复事件模型及其在低血糖中的应用。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae053

Yingfa Xie, Haoda Fu, Yuan Huang, Vladimir Pozdnyakov, Jun Yan

{"title":"Recurrent events modeling based on a reflected Brownian motion with application to hypoglycemia.","authors":"Yingfa Xie, Haoda Fu, Yuan Huang, Vladimir Pozdnyakov, Jun Yan","doi":"10.1093/biostatistics/kxae053","DOIUrl":"10.1093/biostatistics/kxae053","url":null,"abstract":"Patients with type 2 diabetes need to closely monitor blood sugar levels as their routine diabetes self-management. Although many treatment agents aim to tightly control blood sugar, hypoglycemia often stands as an adverse event. In practice, patients can observe hypoglycemic events more easily than hyperglycemic events due to the perception of neurogenic symptoms. We propose to model each patient's observed hypoglycemic event as a lower boundary crossing event for a reflected Brownian motion with an upper reflection barrier. The lower boundary is set by clinical standards. To capture patient heterogeneity and within-patient dependence, covariates and a patient level frailty are incorporated into the volatility and the upper reflection barrier. This framework provides quantification for the underlying glucose level variability, patients heterogeneity, and risk factors' impact on glucose. We make inferences based on a Bayesian framework using Markov chain Monte Carlo. Two model comparison criteria, the deviance information criterion and the logarithm of the pseudo-marginal likelihood, are used for model selection. The methodology is validated in simulation studies. In analyzing a dataset from the diabetic patients in the DURABLE trial, our model provides adequate fit, generates data similar to the observed data, and offers insights that could be missed by other models.","PeriodicalId":55357,"journal":{"name":"Biostatistics","volume":"26 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

The impact of coarsening an exposure on partial identifiability in instrumental variable settings. 在工具变量设置中，粗化暴露对部分可识别性的影响。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae042

Erin E Gabriel, Michael C Sachs, Arvid Sjölander

引用次数: 0

Model-based multifacet clustering with high-dimensional omics applications. 基于模型的多面聚类与高维 omics 应用。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae020

Wei Zong, Danyang Li, Marianne L Seney, Colleen A Mcclung, George C Tseng

引用次数: 0

Fast standard error estimation for joint models of longitudinal and time-to-event data based on stochastic EM algorithms. 基于随机 EM 算法的纵向数据和时间到事件数据联合模型的快速标准误差估计。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae043

Tingting Yu, Lang Wu, Ronald J Bosch, Davey M Smith, Rui Wang

{"title":"Fast standard error estimation for joint models of longitudinal and time-to-event data based on stochastic EM algorithms.","authors":"Tingting Yu, Lang Wu, Ronald J Bosch, Davey M Smith, Rui Wang","doi":"10.1093/biostatistics/kxae043","DOIUrl":"10.1093/biostatistics/kxae043","url":null,"abstract":"Maximum likelihood inference can often become computationally intensive when performing joint modeling of longitudinal and time-to-event data, due to the intractable integrals in the joint likelihood function. The computational challenges escalate further when modeling HIV-1 viral load data, owing to the nonlinear trajectories and the presence of left-censored data resulting from the assay's lower limit of quantification. In this paper, for a joint model comprising a nonlinear mixed-effect model and a Cox Proportional Hazards model, we develop a computationally efficient Stochastic EM (StEM) algorithm for parameter estimation. Furthermore, we propose a novel technique for fast standard error estimation, which directly estimates standard errors from the results of StEM iterations and is broadly applicable to various joint modeling settings, such as those containing generalized linear mixed-effect models, parametric survival models, or joint models with more than two submodels. We evaluate the performance of the proposed methods through simulation studies and apply them to HIV-1 viral load data from six AIDS Clinical Trials Group studies to characterize viral rebound trajectories following the interruption of antiretroviral therapy (ART), accounting for the informative duration of off-ART periods.","PeriodicalId":55357,"journal":{"name":"Biostatistics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11823262/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Speeding up interval estimation for R2-based mediation effect of high-dimensional mediators via cross-fitting. 通过交叉拟合，加快基于 R2 的高维中介效应的区间估计。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae037

Zhichao Xu, Chunlin Li, Sunyi Chi, Tianzhong Yang, Peng Wei

{"title":"Speeding up interval estimation for R2-based mediation effect of high-dimensional mediators via cross-fitting.","authors":"Zhichao Xu, Chunlin Li, Sunyi Chi, Tianzhong Yang, Peng Wei","doi":"10.1093/biostatistics/kxae037","DOIUrl":"10.1093/biostatistics/kxae037","url":null,"abstract":"Mediation analysis is a useful tool in investigating how molecular phenotypes such as gene expression mediate the effect of exposure on health outcomes. However, commonly used mean-based total mediation effect measures may suffer from cancellation of component-wise mediation effects in opposite directions in the presence of high-dimensional omics mediators. To overcome this limitation, we recently proposed a variance-based R-squared total mediation effect measure that relies on the computationally intensive nonparametric bootstrap for confidence interval estimation. In the work described herein, we formulated a more efficient two-stage, cross-fitted estimation procedure for the R2 measure. To avoid potential bias, we performed iterative Sure Independence Screening (iSIS) in two subsamples to exclude the non-mediators, followed by ordinary least squares regressions for the variance estimation. We then constructed confidence intervals based on the newly derived closed-form asymptotic distribution of the R2 measure. Extensive simulation studies demonstrated that this proposed procedure is much more computationally efficient than the resampling-based method, with comparable coverage probability. Furthermore, when applied to the Framingham Heart Study, the proposed method replicated the established finding of gene expression mediating age-related variation in systolic blood pressure and identified the role of gene expression profiles in the relationship between sex and high-density lipoprotein cholesterol level. The proposed estimation procedure is implemented in R package CFR2M.","PeriodicalId":55357,"journal":{"name":"Biostatistics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11823199/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Adaptive Gaussian Markov random fields for child mortality estimation. 用于儿童死亡率估算的自适应高斯马尔可夫随机场。

IF 1.8 3区数学

Biostatistics Pub Date : 2024-12-31 DOI: 10.1093/biostatistics/kxae030

Serge Aleshin-Guendel, Jon Wakefield

引用次数: 0