2023

最新文章

• BAYESIAN COX REGRESSION FOR LARGE-SCALE INFERENCE WITH APPLICATIONS TO ELECTRONIC HEALTH RECORDS AI翻译
  作者：Jung, Alexander Wolfgang; Gerstung, Moritz
  作者单位：European Molecular Biology Laboratory (EMBL); European Bioinformatics Institute; Helmholtz Association; German Cancer Research Center (DKFZ)
  摘要：The Cox model is an indispensable tool for time-to-event analysis, particularly in biomedical research. However, medicine is undergoing a profound transformation, generating data at an unprecedented scale, which opens new frontiers to study and understand diseases. With the wealth of data collected, new challenges for statistical inference arise, as datasets are often high dimensional, exhibit an increasing number of measurements at irregularly spaced time points, and are simply too large to f...
• BAYESIAN NON-HOMOGENEOUS HIDDEN MARKOV MODEL WITH VARIABLE SELECTION FOR INVESTIGATING DRIVERS OF SEIZURE RISK CYCLING AI翻译
  作者：Wang, Emily T.; Chiang, Sharon; Haneef, Zulfi; Rao, Vikram R.; Moss, Robert; Vannucci, Marina
  作者单位：Rice University; University of California System; University of California San Francisco; Baylor College of Medicine
  摘要：A major issue in the clinical management of epilepsy is the unpredictabil-ity of seizures. Yet, traditional approaches to seizure forecasting and risk assessment in epilepsy rely heavily on raw seizure frequencies which are a stochastic measurement of seizure risk. We consider a Bayesian nonhomo-geneous hidden Markov model for unsupervised clustering of zero-inflated seizure count data. The proposed model allows for a probabilistic estimate of the sequence of seizure risk states at the individ...
• JOINT MODELING OF PLAYING TIME AND PURCHASE PROPENSITY IN MASSIVELY MULTIPLAYER ONLINE ROLE-PLAYING GAMES USING CROSSED RANDOM EFFECTS AI翻译
  作者：Banerjee, Trambak; Liu, Peng; Mukherjee, Gourab; Dutta, Shantanu; Che, Hai
  作者单位：University of Kansas; Santa Clara University; University of Southern California; University of Southern California; University of California System; University of California Riverside
  摘要：Massively multiplayer online role-playing games (MMORPGs) offer a unique blend of a personalized gaming experience and a platform for forging social connections. Managers of these digital products rely on predictions of key player responses, such as playing time and purchase propensity, to design timely interventions for promoting, engaging and monetizing their playing base. However, the longitudinal data associated with these MMORPGs not only exhibit a large set of potential predictors to cho...
• A HORSESHOE MIXTURE MODEL FOR BAYESIAN SCREENING WITH AN APPLICATION TO LIGHT SHEET FLUORESCENCE MICROSCOPY IN BRAIN IMAGING AI翻译
  作者：Denti, Francesco; Azevedo, Ricardo; Lo, Chelsie; Wheeler, Damian G.; Gandhi, Sunil P.; Guindani, Michele; Shahbaba, Babak
  作者单位：Catholic University of the Sacred Heart; University of California System; University of California Irvine; University of California System; University of California Los Angeles
  摘要：In this paper we focus on identifying differentially activated brain regions using a light sheet fluorescence microscopy-a recently developed technique for whole-brain imaging. Most existing statistical methods solve this problem by partitioning the brain regions into two classes: significantly and nonsignificantly activated. However, for the brain imaging problem at the center of our study, such binary grouping may provide overly simplistic discoveries by filtering out weak but important sign...
• AN EFFICIENT DOUBLY-ROBUST IMPUTATION FRAMEWORK FOR LONGITUDINAL DROPOUT, WITH AN APPLICATION TO AN ALZHEIMER'S CLINICAL TRIAL AI翻译
  作者：Qiu, Yuqi; Messer, Karen
  作者单位：East China Normal University; University of California System; University of California San Diego
  摘要：We develop a novel doubly-robust (DR) imputation framework for longitudinal studies with monotone dropout, motivated by the informative dropout that is common in FDA-regulated trials for Alzheimer's disease. In this approach the missing data are first imputed using a doubly-robust augmented inverse probability weighting (AIPW) estimator; then the imputed completed data are substituted into a full-data estimating equation, and the estimate is obtained using standard software. The imputed comple...
• SURROGATE MARKER ASSESSMENT USING MEDIATION AND INSTRUMENTAL VARIABLE ANALYSES IN A CASE-COHORT DESIGN AI翻译
  作者：Huang, Yen-tsung; Yu, Jih-chang; Lin, Ui-hsiang
  作者单位：Academia Sinica - Taiwan
  摘要：The identification of surrogate markers for gold standard outcomes in clinical trials enables future cost-effective trials that target the identified markers. Due to resource limitations, these surrogate markers may be collected only for cases and for a subset of the trial cohort, giving rise to what is termed the case-cohort design. Motivated by a COVID-19 vaccine trial, we propose methods of assessing the surrogate markers for a time-to-event outcome in a case-cohort design by using mediatio...
• MODEL-INDEPENDENT DETECTION OF NEW PHYSICS SIGNALS USING INTERPRETABLE SEMISUPERVISED CLASSIFIER TESTS AI翻译
  作者：Chakravarti, Purvasha; Kuusela, Mikael; Lei, Jing; Wasserman, Larry
  作者单位：University of London; University College London; Carnegie Mellon University; Carnegie Mellon University
  摘要：A central goal in experimental high energy physics is to detect new physics signals that are not explained by known physics. In this paper we aim to search for new signals that appear as deviations from known Standard Model physics in high-dimensional particle physics data. To do this, we determine whether there is any statistically significant difference between the distribution of Standard Model background samples and the distribution of the experimental observations which are a mixture of t...
• MODELING BIOMARKER RATIOS WITH GAMMA DISTRIBUTED COMPONENTS (vol 13, page 548, 2019) AI翻译
  作者：Schmid, Matthias
  作者单位：University of Bonn
• ESTIMATING GARCH(1,1) IN THE PRESENCE OF MISSING DATA AI翻译
  作者：Wee, Damien c. h.; Chen, Feng; Dunsmuir, William t. m.
  作者单位：University of New South Wales Sydney
  摘要：Maximum likelihood estimation of the famous GARCH(1, 1) model is generally straightforward, given the full observation series. However, when some observations are missing, the marginal likelihood of the observed data is intractable in most cases of interest, also intractable is the likelihood from temporally aggregated data. For both these problems, we propose to approximate the intractable likelihoods through sequential Monte Carlo (SMC). The SMC approximation is done in a smooth manner so th...
• A BAYESIAN ACCELERATED FAILURE TIME MODEL FOR INTERVAL AI翻译
  作者：Klausch, Thomas; Akwiwu, Eddymurphy U.; van de Wiel, Mark A.; Coupe, Veerle M. H.; Berkhof, Johannes
  作者单位：University of Amsterdam
  摘要：Women infected by the human papillomavirus are at an increased risk to develop cervical intraepithelial neoplasia lesions (CIN). CIN are classified into three grades of increasing severity (CIN-1, CIN-2, and CIN-3) and can eventually develop into cervical cancer. The main purpose of screening is detecting CIN-2 and CIN-3 cases which are usually removed surgically. Screening data from the POBASCAM trial involving 1454 HPV-positive women are analyzed with two objectives, estimate: (a) the transi...