10.9k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
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216 papers · 1 filter
A Frequency-Domain Approach for Integrating Multiple Functional Time Series
Zerui Guo, Jianbin Tan, Hui Huang
Integrative analysis of multivariate functional time series (MFTS) is both critical and challenging across many scientific domains. Such data often exhibit complex multi-way depend…
Weight a Minute: Understanding Variability in PATE Estimates Across Target Populations
William Stewart, Carly L. Brantner, Elizabeth A. Stuart +1
Clinical study populations often differ meaningfully from the broader populations to which results are intended to generalize. Weighting methods such as inverse probability of samp…
Improving Variance and Confidence Interval Estimation in Small-Sample Propensity Score Analyses: Bootstrap vs. Asymptotic Methods
Baoshan Zhang, Sean M. O'Brien, Yuan Wu +1
Propensity score (PS) methods are widely used to estimate treatment effects in non-randomized studies. Variance is typically estimated using sandwich or bootstrap methods, which ca…
Local graph estimation with pathwise false discovery control
Omar Melikechi, David B. Dunson, Noureddine Melikechi +1
Many datasets include a small set of variables, such as biomarkers or clinical outcomes, whose relationships to the broader system are of primary scientific interest. Estimating th…
Joint space-time modelling for upper daily maximum and minimum temperature record-breaking
Jorge Castillo-Mateo, Zeus Gracia-Tabuenca, Jesús Asín +2
Record-breaking temperature events are now frequently in the news, proffered as evidence of climate change, and often bring significant economic and human impacts. Our previous wor…
On prior smoothing with discrete spatial data in the context of disease mapping
Garazi Retegui, Alan E. Gelfand, Jaione Etxeberria +1
Disease mapping attempts to explain observed health event counts across areal units, typically using Markov random field models. These models rely on spatial priors to account for…
Rejoinder to Reader Reaction "On exact randomization-based covariate-adjusted confidence intervals" by Jacob Fiksel
Ke Zhu, Hanzhong Liu
We applaud Fiksel (2024) for their valuable contributions to randomization-based inference, particularly their work on inverting the Fisher randomization test (FRT) to construct co…
Supervised low-rank approximation of high-dimensional multivariate functional data via tensor decomposition
Mohammad Samsul Alam, Ana-Maria Staicu, Pixu Shi
Motivated by the challenges of analyzing high-dimensional () sequencing data from longitudinal microbiome studies, where samples are collected at multiple time points from…
A novel longitudinal rank-sum test for multiple primary endpoints in clinical trials: Applications to neurodegenerative disorders
Xiaoming Xu, Dhrubajyoti Ghosh, Sheng Luo
Neurodegenerative disorders such as Alzheimer's disease (AD) present a significant global health challenge, characterized by cognitive decline, functional impairment, and other deb…
Robust Score-Based Quickest Change Detection
Sean Moushegian, Suya Wu, Enmao Diao +3
Methods in the field of quickest change detection rapidly detect in real-time a change in the data-generating distribution of an online data stream. Existing methods have been able…
A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events using patient registry data
Pedro Miranda Afonso, Dimitris Rizopoulos, Anushka K. Palipana +5
Joint models for longitudinal and survival data have become a popular framework for studying the association between repeatedly measured biomarkers and clinical events. Nevertheles…
Interval-censored linear quantile regression
Taehwa Choi, Seohyeon Park, Hunyong Cho +1
Censored quantile regression has emerged as a prominent alternative to classical Cox's proportional hazards model or accelerated failure time model in both theoretical and applied…
Spatio-temporal modeling for record-breaking temperature events in Spain
Jorge Castillo-Mateo, Alan E. Gelfand, Zeus Gracia-Tabuenca +2
Record-breaking temperature events are now very frequently in the news, viewed as evidence of climate change. With this as motivation, we undertake the first substantial spatial mo…
Evaluating Binary Outcome Classifiers Estimated from Survey Data
Adway S. Wadekar, Jerome P. Reiter
Surveys are commonly used to facilitate research in epidemiology, health, and the social and behavioral sciences. Often, these surveys are not simple random samples, and respondent…
Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes
Xueqing Liu, Tianchen Qian, Lauren Bell +1
In mobile health, tailoring interventions for real-time delivery is of paramount importance. Micro-randomized trials have emerged as the "gold-standard" methodology for developing…
A Double Machine Learning Approach to Combining Experimental and Observational Data
Harsh Parikh, Marco Morucci, Vittorio Orlandi +3
Experimental and observational studies often lack validity due to untestable assumptions. We propose a double machine learning approach to combine experimental and observational st…
Bayesian joint quantile autoregression
Jorge Castillo-Mateo, Alan E. Gelfand, Jesús Asín +2
Quantile regression continues to increase in usage, providing a useful alternative to customary mean regression. Primary implementation takes the form of so-called multiple quantil…
Exploring the validity of the complete case analysis for regression models with a right-censored covariate
Marissa C. Ashner, Tanya P. Garcia
Despite its drawbacks, the complete case analysis is commonly used in regression models with missing covariates. Understanding when implementing complete cases will lead to consist…
Projection-based two-sample inference for sparsely observed multivariate functional data
Salil Koner, Sheng Luo
Modern longitudinal studies collect multiple outcomes as the primary endpoints to understand the complex dynamics of the diseases. Oftentimes, especially in clinical trials, the jo…
Bayesian Graphical Entity Resolution Using Exchangeable Random Partition Priors
Neil G. Marchant, Benjamin I. P. Rubinstein, Rebecca C. Steorts
Entity resolution (record linkage or deduplication) is the process of identifying and linking duplicate records in databases. In this paper, we propose a Bayesian graphical approac…
Model-based tools for assessing space and time change in daily maximum temperature: an application to the Ebro basin in Spain
Ana C. Cebrián, Jesús Asín, Jorge Castillo-Mateo +2
There is continuing interest in the investigation of change in temperature over space and time. We offer a set of tools to illuminate such change temporally, at desired temporal re…
Heavy-Tailed Density Estimation
Surya T Tokdar, Sheng Jiang, Erika L Cunningham
A novel statistical method is proposed and investigated for estimating a heavy tailed density under mild smoothness assumptions. Statistical analyses of heavy-tailed distributions…
Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials
Xinru Wang, Nina Deliu, Yusuke Narita +1
Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential multiple assignment r…
Generalized Bayes Approach to Inverse Problems with Model Misspecification
Youngsoo Baek, Wilkins Aquino, Sayan Mukherjee
We propose a general framework for obtaining probabilistic solutions to PDE-based inverse problems. Bayesian methods are attractive for uncertainty quantification but assume knowle…