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最新文章

• A TENSOR DECOMPOSITION MODEL FOR LONGITUDINAL MICROBIOME STUDIES AI翻译
  作者：Ma, Siyuan; Li, Hongzhe
  作者单位：University of Pennsylvania
  摘要：Longitudinal microbiome studies can help delineate true biological signals from the high interindividual variability that is common in microbiome data. However, there are few methods available for unsupervised dimension reduction of time course microbial abundance observations. Existing methods do not fully observe the distribution characteristics of such data types, namely, zero inflation, compositionality, and overdispersion. We present a tensor decomposition model and a semiparametric quasi...
• LATENT MULTIVARIATE LOG-GAMMA MODELS FOR HIGH-DIMENSIONAL MULTITYPE RESPONSES WITH APPLICATION TO DAILY FINE PARTICULATE MATTER AND MORTALITY COUNTS AI翻译
  作者：Xu, Zhixing; Bradley, Jonathan R.; Sinha, Debajyoti
  作者单位：State University System of Florida; Florida State University
  摘要：Precise estimation of daily fine particulate matter with a diameter < 2.5 microns (PM2.5) and mortality in the U.S. is an important research challenge in public health because high levels of PM2.5 have been linked to several serious health problems, including lung disease, cardiovascular disease, and stroke. This motivates us to develop a joint Bayesian hierarchical model for bivariate spatial data to obtain precise spatial predictions of two types of re-sponses, continuous skewed PM2.5 levels...
• THE RISK OF MATERNAL COMPLICATIONS AFTER CESAREAN DELIVERY: NEAR-FAR MATCHING FOR INSTRUMENTAL VARIABLES STUDY DESIGNS WITH LARGE OBSERVATIONAL DATASETS AI翻译
  作者：Lu, Ruoqi; Kelz, Rachel; Lorch, Scott; Keele, Luke J.
  作者单位：University of California System; University of California Davis; University of Pennsylvania; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia
  摘要：Cesarean delivery is used when there are problems with the placenta or umbilical cord, for twin pregnancies, and breech births. However, research has found that Cesarean delivery increases the risk of maternal complications like blood transfusions and admission to the intensive care unit. Here, us-ing an instrumental variables study design to reduce bias from unobserved confounders, we study whether Cesarean delivery increases the risk of ma-ternal complications. We use a variant of matching-n...
• BAYESIAN ANALYSIS FOR IMBALANCED POSITIVE-UNLABELLED DIAGNOSIS CODES IN ELECTRONIC HEALTH RECORDS AI翻译
  作者：Wang, By Ru; Liang, Ye; Miao, Zhuqi; Liu, Tieming
  作者单位：Oklahoma State University System; Oklahoma State University - Stillwater; State University of New York (SUNY) System; SUNY New Paltz; Oklahoma State University System; Oklahoma State University - Stillwater
  摘要：With the increasing availability of electronic health records (EHR), sig-nificant progress has been made on developing predictive inference and al-gorithms by health-data analysts and researchers. However, the EHR data are notoriously noisy, due to missing and inaccurate inputs, despite abundant in-formation. One serious problem is that only a small portion of patients in the database has confirmatory diagnoses, while many other patients remain undiagnosed because they did not comply with the ...
• ESTIMATING GLOBAL AND COUNTRY-SPECIFIC EXCESS MORTALITY DURING THE COVID-19 PANDEMIC AI翻译
  作者：Knutson, Victoria; Aleshin-Guendel, Serge; Karlinsky, Ariel; Msemburi, William; Wakefield, Jon
  作者单位：University of Washington; University of Washington Seattle; Hebrew University of Jerusalem; Hebrew University of Jerusalem; World Health Organization; University of Washington; University of Washington Seattle
  摘要：Estimating the true mortality burden of COVID-19 for every country in the world is a difficult, but crucial, public health endeavor. Attributing deaths, direct or indirect, to COVID-19 is problematic. A more attainable target is the excess deaths, the number of deaths in a particular period, relative to that expected during normal times, and we develop a model for this endeavor. The excess mortality requires two numbers, the total deaths and the expected deaths, but the former is unavailable f...
• DETECTING DISTRIBUTIONAL DIFFERENCES IN LABELED SEQUENCE DATA WITH APPLICATION TO TROPICAL CYCLONE SATELLITE IMAGERY AI翻译
  作者：Mcneely, Trey; Vincent, Galen; Wood, Kimberly M.; Izbicki, Rafael; Lee, Ann B.
  作者单位：Carnegie Mellon University; Mississippi State University; Universidade Federal de Sao Carlos
  摘要：Our goal is to quantify whether, and if so how, spatiotemporal patterns in tropical cyclone (TC) satellite imagery signal an upcoming rapid intensity change event. To address this question, we propose a new nonparametric test of association between a time series of images and a series of binary event la-bels. We ask whether there is a difference in distribution between (dependent but identically distributed) 24-hour sequences of images preceding an event vs. a nonevent. By rewriting the statis...
• BAYESIAN DECISION THEORY FOR TREE-BASED ADAPTIVE SCREENING TESTS WITH AN APPLICATION TO YOUTH DELINQUENCY AI翻译
  作者：Krantsevich, Chelsea; Hahn, P. Richard; Zheng, Yi; Katz, Charles
  作者单位：Arizona State University; Arizona State University-Tempe; Arizona State University; Arizona State University-Tempe
  摘要：Crime prevention strategies based on early intervention depend on accu-rate risk assessment instruments for identifying high-risk youth. It is impor-tant in this context that the instruments be convenient to administer, which means, in particular, that they should also be reasonably brief; adaptive screening tests are useful for this purpose. Adaptive tests constructed using classification and regression trees are becoming a popular alternative to tradi-tional item response theory (IRT) approa...
• VARIATIONAL BAYESIAN ANALYSIS OF NONHOMOGENEOUS HIDDEN MARKOV MODELS WITH LONG AND ULTRALONG SEQUENCES AI翻译
  作者：Chen, Xinyuan; Li, Yiwei; Feng, Xiangnan; Chang, Joseph T.
  作者单位：Mississippi State University; Lingnan University; Fudan University; Yale University
  摘要：Nonhomogeneous hidden Markov models (NHMMs) are useful in mod-eling sequential and autocorrelated data. Bayesian approaches, particularly Markov chain Monte Carlo (MCMC) methods, are principal statistical in-ference tools for NHMMs. However, MCMC sampling is computationally demanding, especially for long observation sequences. We develop a vari-ational Bayes (VB) method for NHMMs, which utilizes a structured varia-tional family of Gaussian distributions with factorized covariance matrices to a...
• ESTIMATION AND INFERENCE FOR EXPOSURE EFFECTS WITH LATENCY IN THE COX PROPORTIONAL HAZARDS MODEL IN THE PRESENCE OF EXPOSURE MEASUREMENT ERROR AI翻译
  作者：Peskoe, Sarah B.; Zhang, Ning; Spiegelman, Donna; Wang, Molin
  作者单位：Duke University; Harvard University; Harvard T.H. Chan School of Public Health; Yale University
  摘要：Researchers are often interested in estimating the effects of time-varying exposures on health outcomes. The latency period, defined as the critical pe-riod of susceptibility, can be an important component of exposure effect as-sessment. Although it is widely known that many environmental, nutritional, and other exposure measurements are prone to error and are also likely to act only during a critical time window of susceptibility, no one has yet considered the impact of this on the estimation...
• BIVARIATE HIERARCHICAL BAYESIAN MODEL FOR COMBINING SUMMARY MEASURES AND THEIR UNCERTAINTIES FROM MULTIPLE SOURCES AI翻译
  作者：Yao, Yujing; Ogden, R. Todd; Zeng, Chubing; Chen, Qixuan
  作者单位：Columbia University; University of Southern California
  摘要：It is often of interest to combine available estimates of a similar quantity from multiple data sources. When the corresponding variances of each esti-mate are also available, a model should take into account the uncertainty of the estimates themselves as well as the uncertainty in the estimation of vari-ances. In addition, if there exists a strong association between estimates and their variances, the correlation between these two quantities should also be considered. In this paper we propose...