Annals of Applied Statistics最新文献_第2页

A BAYESIAN MACHINE LEARNING APPROACH FOR ESTIMATING HETEROGENEOUS SURVIVOR CAUSAL EFFECTS: APPLICATIONS TO A CRITICAL CARE TRIAL. 估计异质幸存者因果效应的贝叶斯机器学习方法：应用于重症监护试验。

IF 1.8 4区数学

Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI: 10.1214/23-aoas1792

Xinyuan Chen, Michael O Harhay, Guangyu Tong, Fan Li

{"title":"A BAYESIAN MACHINE LEARNING APPROACH FOR ESTIMATING HETEROGENEOUS SURVIVOR CAUSAL EFFECTS: APPLICATIONS TO A CRITICAL CARE TRIAL.","authors":"Xinyuan Chen, Michael O Harhay, Guangyu Tong, Fan Li","doi":"10.1214/23-aoas1792","DOIUrl":"10.1214/23-aoas1792","url":null,"abstract":"Assessing heterogeneity in the effects of treatments has become increasingly popular in the field of causal inference and carries important implications for clinical decision-making. While extensive literature exists for studying treatment effect heterogeneity when outcomes are fully observed, there has been limited development in tools for estimating heterogeneous causal effects when patient-centered outcomes are truncated by a terminal event, such as death. Due to mortality occurring during study follow-up, the outcomes of interest are unobservable, undefined, or not fully observed for many participants in which case principal stratification is an appealing framework to draw valid causal conclusions. Motivated by the Acute Respiratory Distress Syndrome Network (ARDSNetwork) ARDS respiratory management (ARMA) trial, we developed a flexible Bayesian machine learning approach to estimate the average causal effect and heterogeneous causal effects among the always-survivors stratum when clinical outcomes are subject to truncation. We adopted Bayesian additive regression trees (BART) to flexibly specify separate mean models for the potential outcomes and latent stratum membership. In the analysis of the ARMA trial, we found that the low tidal volume treatment had an overall benefit for participants sustaining acute lung injuries on the outcome of time to returning home but substantial heterogeneity in treatment effects among the always-survivors, driven most strongly by biologic sex and the alveolar-arterial oxygen gradient at baseline (a physiologic measure of lung function and degree of hypoxemia). These findings illustrate how the proposed methodology could guide the prognostic enrichment of future trials in the field.","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"18 1","pages":"350-374"},"PeriodicalIF":1.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10919396/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140061169","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 SIMPLE AND FLEXIBLE TEST OF SAMPLE EXCHANGEABILITY WITH APPLICATIONS TO STATISTICAL GENOMICS. 简单灵活的样本可交换性测试，应用于统计基因组学。

IF 1.8 4区数学

Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI: 10.1214/23-aoas1817

Alan J Aw, Jeffrey P Spence, Yun S Song

{"title":"A SIMPLE AND FLEXIBLE TEST OF SAMPLE EXCHANGEABILITY WITH APPLICATIONS TO STATISTICAL GENOMICS.","authors":"Alan J Aw, Jeffrey P Spence, Yun S Song","doi":"10.1214/23-aoas1817","DOIUrl":"10.1214/23-aoas1817","url":null,"abstract":"In scientific studies involving analyses of multivariate data, basic but important questions often arise for the researcher: Is the sample exchangeable, meaning that the joint distribution of the sample is invariant to the ordering of the units? Are the features independent of one another, or perhaps the features can be grouped so that the groups are mutually independent? In statistical genomics, these considerations are fundamental to downstream tasks such as demographic inference and the construction of polygenic risk scores. We propose a non-parametric approach, which we call the V test, to address these two questions, namely, a test of sample exchangeability given dependency structure of features, and a test of feature independence given sample exchangeability. Our test is conceptually simple, yet fast and flexible. It controls the Type I error across realistic scenarios, and handles data of arbitrary dimensions by leveraging large-sample asymptotics. Through extensive simulations and a comparison against unsupervised tests of stratification based on random matrix theory, we find that our test compares favorably in various scenarios of interest. We apply the test to data from the 1000 Genomes Project, demonstrating how it can be employed to assess exchangeability of the genetic sample, or find optimal linkage disequilibrium (LD) splits for downstream analysis. For exchangeability assessment, we find that removing rare variants can substantially increase the <math><mi>p</mi></math>-value of the test statistic. For optimal LD splitting, the V test reports different optimal splits than previous approaches not relying on hypothesis testing. Software for our methods is available in R (CRAN: flintyR) and Python (PyPI: flintyPy).","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"18 1","pages":"858-881"},"PeriodicalIF":1.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11115382/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141089297","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

USING SIMULTANEOUS REGRESSION CALIBRATION TO STUDY THE EFFECT OF MULTIPLE ERROR-PRONE EXPOSURES ON DISEASE RISK UTILIZING BIOMARKERS DEVELOPED FROM A CONTROLLED FEEDING STUDY. 使用同步回归校准法，利用受控喂养研究中开发的生物标记物，研究多种易出错暴露对疾病风险的影响。

IF 1.3 4区数学

Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI: 10.1214/23-aoas1782

Yiwen Zhang, Ran Dai, Ying Huang, Ross Prentice, Cheng Zheng

{"title":"USING SIMULTANEOUS REGRESSION CALIBRATION TO STUDY THE EFFECT OF MULTIPLE ERROR-PRONE EXPOSURES ON DISEASE RISK UTILIZING BIOMARKERS DEVELOPED FROM A CONTROLLED FEEDING STUDY.","authors":"Yiwen Zhang, Ran Dai, Ying Huang, Ross Prentice, Cheng Zheng","doi":"10.1214/23-aoas1782","DOIUrl":"10.1214/23-aoas1782","url":null,"abstract":"Systematic measurement error in self-reported data creates important challenges in association studies between dietary intakes and chronic disease risks, especially when multiple dietary components are studied jointly. The joint regression calibration method has been developed for measurement error correction when objectively measured biomarkers are available for all dietary components of interest. Unfortunately, objectively measured biomarkers are only available for very few dietary components, which limits the application of the joint regression calibration method. Recently, for single dietary components, controlled feeding studies have been performed to develop new biomarkers for many more dietary components. However, it is unclear whether the biomarkers separately developed for single dietary components are valid for joint calibration. In this paper, we show that biomarkers developed for single dietary components cannot be used for joint regression calibration. We propose new methods to utilize controlled feeding studies to develop valid biomarkers for joint regression calibration to estimate the association between multiple dietary components simultaneously with the disease of interest. Asymptotic distribution theory for the proposed estimators is derived. Extensive simulations are performed to study the finite sample performance of the proposed estimators. We apply our methods to examine the joint effects of sodium and potassium intakes on cardiovascular disease incidence using the Women's Health Initiative cohort data. We identify positive associations between sodium intake and cardiovascular diseases as well as negative associations between potassium intake and cardiovascular disease.","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"18 1","pages":"125-143"},"PeriodicalIF":1.3,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10836829/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139681864","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

LATENT SUBGROUP IDENTIFICATION IN IMAGE-ON-SCALAR REGRESSION. 图像标度回归中的潜在子群识别。

IF 1.8 4区数学

Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI: 10.1214/23-aoas1797

Zikai Lin, Yajuan Si, Jian Kang

{"title":"LATENT SUBGROUP IDENTIFICATION IN IMAGE-ON-SCALAR REGRESSION.","authors":"Zikai Lin, Yajuan Si, Jian Kang","doi":"10.1214/23-aoas1797","DOIUrl":"10.1214/23-aoas1797","url":null,"abstract":"Image-on-scalar regression has been a popular approach to modeling the association between brain activities and scalar characteristics in neuroimaging research. The associations could be heterogeneous across individuals in the population, as indicated by recent large-scale neuroimaging studies, for example, the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD data can inform our understanding of heterogeneous associations and how to leverage the heterogeneity and tailor interventions to increase the number of youths who benefit. It is of great interest to identify subgroups of individuals from the population such that: (1) within each subgroup the brain activities have homogeneous associations with the clinical measures; (2) across subgroups the associations are heterogeneous, and (3) the group allocation depends on individual characteristics. Existing image-on-scalar regression methods and clustering methods cannot directly achieve this goal. We propose a latent subgroup image-on-scalar regression model (LASIR) to analyze large-scale, multisite neuroimaging data with diverse sociode-mographics. LASIR introduces the latent subgroup for each individual and group-specific, spatially varying effects, with an efficient stochastic expectation maximization algorithm for inferences. We demonstrate that LASIR outperforms existing alternatives for subgroup identification of brain activation patterns with functional magnetic resonance imaging data via comprehensive simulations and applications to the ABCD study. We have released our reproducible codes for public use with the software package available on Github.","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"18 1","pages":"468-486"},"PeriodicalIF":1.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11156244/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141285216","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

ANOPOW FOR REPLICATED NONSTATIONARY TIME SERIES IN EXPERIMENTS. 用于实验中复制的非平稳时间序列的 anopow。

IF 1.8 4区数学

Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI: 10.1214/23-aoas1791

Zeda Li, Yu Ryan Yue, Scott A Bruce

{"title":"ANOPOW FOR REPLICATED NONSTATIONARY TIME SERIES IN EXPERIMENTS.","authors":"Zeda Li, Yu Ryan Yue, Scott A Bruce","doi":"10.1214/23-aoas1791","DOIUrl":"10.1214/23-aoas1791","url":null,"abstract":"We propose a novel analysis of power (ANOPOW) model for analyzing replicated nonstationary time series commonly encountered in experimental studies. Based on a locally stationary ANOPOW Cramér spectral representation, the proposed model can be used to compare the second-order time-varying frequency patterns among different groups of time series and to estimate group effects as functions of both time and frequency. Formulated in a Bayesian framework, independent two-dimensional second-order random walk (RW2D) priors are assumed on each of the time-varying functional effects for flexible and adaptive smoothing. A piecewise stationary approximation of the nonstationary time series is used to obtain localized estimates of time-varying spectra. Posterior distributions of the time-varying functional group effects are then obtained via integrated nested Laplace approximations (INLA) at a low computational cost. The large-sample distribution of local periodograms can be appropriately utilized to improve estimation accuracy since INLA allows modeling of data with various types of distributions. The usefulness of the proposed model is illustrated through two real data applications: analyses of seismic signals and pupil diameter time series in children with attention deficit hyperactivity disorder. Simulation studies, Supplementary Materials (Li, Yue and Bruce, 2023a), and R code (Li, Yue and Bruce, 2023b) for this article are also available.","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"18 1","pages":"328-349"},"PeriodicalIF":1.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10906746/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023131","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

LAND-USE FILTERING FOR NONSTATIONARY SPATIAL PREDICTION OF COLLECTIVE EFFICACY IN AN URBAN ENVIRONMENT. 利用土地利用滤波技术对城市环境中的集体效能进行非稳态空间预测。

IF 1.8 4区数学

Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI: 10.1214/23-aoas1813

J Brandon Carter, Christopher R Browning, Bethany Boettner, Nicolo Pinchak, Catherine A Calder

{"title":"LAND-USE FILTERING FOR NONSTATIONARY SPATIAL PREDICTION OF COLLECTIVE EFFICACY IN AN URBAN ENVIRONMENT.","authors":"J Brandon Carter, Christopher R Browning, Bethany Boettner, Nicolo Pinchak, Catherine A Calder","doi":"10.1214/23-aoas1813","DOIUrl":"10.1214/23-aoas1813","url":null,"abstract":"Collective efficacy-the capacity of communities to exert social control toward the realization of their shared goals-is a foundational concept in the urban sociology and neighborhood effects literature. Traditionally, empirical studies of collective efficacy use large sample surveys to estimate collective efficacy of different neighborhoods within an urban setting. Such studies have demonstrated an association between collective efficacy and local variation in community violence, educational achievement, and health. Unlike traditional collective efficacy measurement strategies, the Adolescent Health and Development in Context (AHDC) Study implemented a new approach, obtaining spatially-referenced, place-based ratings of collective efficacy from a representative sample of individuals residing in Columbus, OH. In this paper we introduce a novel nonstationary spatial model for interpolation of the AHDC collective efficacy ratings across the study area, which leverages administrative data on land use. Our constructive model specification strategy involves dimension expansion of a latent spatial process and the use of a filter defined by the land-use partition of the study region to connect the latent multivariate spatial process to the observed ordinal ratings of collective efficacy. Careful consideration is given to the issues of parameter identifiability, computational efficiency of an MCMC algorithm for model fitting, and fine-scale spatial prediction of collective efficacy.","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"18 1","pages":"794-818"},"PeriodicalIF":1.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11146085/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141238803","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

RETROSPECTIVE VARYING COEFFICIENT ASSOCIATION ANALYSIS OF LONGITUDINAL BINARY TRAITS: APPLICATION TO THE IDENTIFICATION OF GENETIC LOCI ASSOCIATED WITH HYPERTENSION. 纵向二元性状的回顾性变化系数关联分析：应用于确定与高血压相关的遗传位点。

IF 1.3 4区数学

Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI: 10.1214/23-aoas1798

Gang Xu, Amei Amei, Weimiao Wu, Yunqing Liu, Linchuan Shen, Edwin C Oh, Zuoheng Wang

{"title":"RETROSPECTIVE VARYING COEFFICIENT ASSOCIATION ANALYSIS OF LONGITUDINAL BINARY TRAITS: APPLICATION TO THE IDENTIFICATION OF GENETIC LOCI ASSOCIATED WITH HYPERTENSION.","authors":"Gang Xu, Amei Amei, Weimiao Wu, Yunqing Liu, Linchuan Shen, Edwin C Oh, Zuoheng Wang","doi":"10.1214/23-aoas1798","DOIUrl":"10.1214/23-aoas1798","url":null,"abstract":"Many genetic studies contain rich information on longitudinal phenotypes that require powerful analytical tools for optimal analysis. Genetic analysis of longitudinal data that incorporates temporal variation is important for understanding the genetic architecture and biological variation of complex diseases. Most of the existing methods assume that the contribution of genetic variants is constant over time and fail to capture the dynamic pattern of disease progression. However, the relative influence of genetic variants on complex traits fluctuates over time. In this study, we propose a retrospective varying coefficient mixed model association test, RVMMAT, to detect time-varying genetic effect on longitudinal binary traits. We model dynamic genetic effect using smoothing splines, estimate model parameters by maximizing a double penalized quasi-likelihood function, design a joint test using a Cauchy combination method, and evaluate statistical significance via a retrospective approach to achieve robustness to model misspecification. Through simulations we illustrated that the retrospective varying-coefficient test was robust to model misspecification under different ascertainment schemes and gained power over the association methods assuming constant genetic effect. We applied RVMMAT to a genome-wide association analysis of longitudinal measure of hypertension in the Multi-Ethnic Study of Atherosclerosis. Pathway analysis identified two important pathways related to G-protein signaling and DNA damage. Our results demonstrated that RVMMAT could detect biologically relevant loci and pathways in a genome scan and provided insight into the genetic architecture of hypertension.","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"18 1","pages":"487-505"},"PeriodicalIF":1.3,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10994004/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140868741","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

COMPOSITE SCORES FOR TRANSPLANT CENTER EVALUATION: A NEW INDIVIDUALIZED EMPIRICAL NULL METHOD. 用于移植中心评估的综合评分：一种新的个性化经验无效法。

IF 1.3 4区数学

Annals of Applied Statistics Pub Date : 2024-03-01 Epub Date: 2024-01-31 DOI: 10.1214/23-aoas1809

Nicholas Hartman, Joseph M Messana, Jian Kang, Abhijit S Naik, Tempie H Shearon, Kevin He

{"title":"COMPOSITE SCORES FOR TRANSPLANT CENTER EVALUATION: A NEW INDIVIDUALIZED EMPIRICAL NULL METHOD.","authors":"Nicholas Hartman, Joseph M Messana, Jian Kang, Abhijit S Naik, Tempie H Shearon, Kevin He","doi":"10.1214/23-aoas1809","DOIUrl":"10.1214/23-aoas1809","url":null,"abstract":"Risk-adjusted quality measures are used to evaluate healthcare providers with respect to national norms while controlling for factors beyond their control. Existing healthcare provider profiling approaches typically assume that the between-provider variation in these measures is entirely due to meaningful differences in quality of care. However, in practice, much of the between-provider variation will be due to trivial fluctuations in healthcare quality, or unobservable confounding risk factors. If these additional sources of variation are not accounted for, conventional methods will disproportionately identify larger providers as outliers, even though their departures from the national norms may not be \"extreme\" or clinically meaningful. Motivated by efforts to evaluate the quality of care provided by transplant centers, we develop a composite evaluation score based on a novel individualized empirical null method, which robustly accounts for overdispersion due to unobserved risk factors, models the marginal variance of standardized scores as a function of the effective sample size, and only requires the use of publicly-available center-level statistics. The evaluations of United States kidney transplant centers based on the proposed composite score are substantially different from those based on conventional methods. Simulations show that the proposed empirical null approach more accurately classifies centers in terms of quality of care, compared to existing methods.","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"18 1","pages":"729-748"},"PeriodicalIF":1.3,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11395314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142300086","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 RIEMANN MANIFOLD MODEL FRAMEWORK FOR LONGITUDINAL CHANGES IN PHYSICAL ACTIVITY PATTERNS. 体育活动模式纵向变化的里曼流形模型框架。

IF 1.8 4区数学

Annals of Applied Statistics Pub Date : 2023-12-01 Epub Date: 2023-10-30 DOI: 10.1214/23-aoas1758

Jingjing Zou, Tuo Lin, Chongzhi Di, John Bellettiere, Marta M Jankowska, Sheri J Hartman, Dorothy D Sears, Andrea Z LaCroix, Cheryl L Rock, Loki Natarajan

{"title":"A RIEMANN MANIFOLD MODEL FRAMEWORK FOR LONGITUDINAL CHANGES IN PHYSICAL ACTIVITY PATTERNS.","authors":"Jingjing Zou, Tuo Lin, Chongzhi Di, John Bellettiere, Marta M Jankowska, Sheri J Hartman, Dorothy D Sears, Andrea Z LaCroix, Cheryl L Rock, Loki Natarajan","doi":"10.1214/23-aoas1758","DOIUrl":"10.1214/23-aoas1758","url":null,"abstract":"Physical activity (PA) is significantly associated with many health outcomes. The wide usage of wearable accelerometer-based activity trackers in recent years has provided a unique opportunity for in-depth research on PA and its relations with health outcomes and interventions. Past analysis of activity tracker data relies heavily on aggregating minute-level PA records into day-level summary statistics in which important information of PA temporal/diurnal patterns is lost. In this paper we propose a novel functional data analysis approach based on Riemann manifolds for modeling PA and its longitudinal changes. We model smoothed minute-level PA of a day as one-dimensional Riemann manifolds and longitudinal changes in PA in different visits as deformations between manifolds. The variability in changes of PA among a cohort of subjects is characterized via variability in the deformation. Functional principal component analysis is further adopted to model the deformations, and PC scores are used as a proxy in modeling the relation between changes in PA and health outcomes and/or interventions. We conduct comprehensive analyses on data from two clinical trials: Reach for Health (RfH) and Metabolism, Exercise and Nutrition at UCSD (MENU), focusing on the effect of interventions on longitudinal changes in PA patterns and how different modes of changes in PA influence weight loss, respectively. The proposed approach reveals unique modes of changes, including overall enhanced PA, boosted morning PA, and shifts of active hours specific to each study cohort. The results bring new insights into the study of longitudinal changes in PA and health and have the potential to facilitate designing of effective health interventions and guidelines.","PeriodicalId":50772,"journal":{"name":"Annals of Applied Statistics","volume":"17 4","pages":"3216-3240"},"PeriodicalIF":1.8,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11149895/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141249006","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

PAIRWISE NONLINEAR DEPENDENCE ANALYSIS OF GENOMIC DATA. 基因组数据的两两非线性相关性分析。

IF 1.8 4区数学

Annals of Applied Statistics Pub Date : 2023-12-01 Epub Date: 2023-10-30 DOI: 10.1214/23-aoas1745

Siqi Xiang, Wan Zhang, Siyao Liu, Katherine A Hoadley, Charles M Perou, Kai Zhang, J S Marron

引用次数: 0