Papers to Appear

Cover image: The goal of next generation sequencing (NGS) studies is to identify rare genetic variants associated with human diseases. Because the power to identify single genetic variants is low, recent statistical methods focus on modeling the count of rare variants within a chromosomal region of interest (for example a gene) across individuals. The left panel displays a region of the chromosome. The rows correspond to individuals and the columns to positions along this region. The color of the bars indicates whether an individual carries 2 copies (dark blue), 1 copy (cyan) or 0 copy (grey) of a rare genetic variant at a given position. The right panel illustrates the principle of a test statistic that the authors developed, which consists in comparing the number of rare variants (variable x) in the region of interest between individuals who have a disease (cases) to those who do not have the disease (controls). This comes from Figure 1 in the article authored by Jingxiong Xu, Wei Xu, and Laurent Briollais, and entitled "A Bayes factor approach with informative prior for rare genetic variant analysis from next generation sequencing data."


Report of the Editors - 2020


Biometric Methodology


Discussion Papers


Nonparametric variable importance assessment using machine learning techniques

Brian D. Williamson, Peter B. Gilbert, Noah Simon, and Marco Carone


Discussion

Min Lu and Hemant Ishwaran


Rejoinder

Brian D. Williamson, Peter B. Gilbert, Noah Simon, and Marco Carone


Approval policies for modifications to machine learning-based software as a medical device: A study of bio-creep

Jean Feng, Scott Emerson, and Noah Simon


Discussion

Gene Pennello, Berkman Sahiner, Alexej Gossmann, and Nicholas Petrick


Discussion

Sherri Rose


Rejoinder

Jean Feng, Scott Emerson, and Noah Simon


Analyzing wearable device data using marked point processes

Yuchen Yang and Mei-Cheng Wang


Case contamination in electronic health records-based case-control studies

Lu Wang, Jill Schnall, Aeron Small, Rebecca A. Hubbard, Jason H. Moore, Scott M. Damrauer, and Jinbo Chen


Bayesian latent multi-state modeling for non-equidistant longitudinal electronic health records

Y. Luo, D. A. Stephens, A. Verma, and D. L. Buckeridge


Zero-inflated Poisson Factor Model with Application to Microbiome Read Counts

Tianchen Xu, Ryan T. Demmer, and Gen Li


Retrospective score tests versus prospective score tests for genetic association with case-control data

Yukun Liu, Pengfei Li, Lei Song, Kai Yu, and Jing Qin


On computation of semi-parametric maximum likelihood estimators with shape constraints

Yudong Wang, Zhi-Sheng Ye, and Hongyuan Cao


A Bayesian nonparametric model for zero-inflated outcomes: prediction, clustering, and causal estimation

Arman Oganisian, Nandita Mitra, and Jason A. Roy


Bayesian inference of causal effects from observational data in Gaussian graphical models

Federico Castelletti, and Guido Consonni


A Joint Modeling Approach for Analyzing Marker Data in the Presence of a Terminal Event

Jie Zhou, Xin Chen, Xinyuan Song, and Liuquan Sun


Weighted regression analysis to correct for informative monitoring times and confounders in longitudinal studies

Janie Coulombe, Erica E. M. Moodie, and Robert W. Platt


Dynamic inference in general nested case-control designs

J. Feifel and D. Dobler


Parameter estimation for discretely-observed linear birth-and-death processes

Anthony Davison, Sophie Hautphenne, and Andrea Kraus


Transporting stochastic direct and indirect effects to new populations

Kara E. Rudolph, Jonathan Levy, and Mark J. van der Laan


A powerful procedure that controls the false discovery rate with directional information

Zhaoyang Tian, Kun Liang, and Pengfei Li


Adaptive treatment and robust control

Q. Clairon, R. Henderson, N. J. Young, E. D. Wilson, and C. J. Taylor


Upper bound estimators of the population size based on ordinal models for capture-recapture experiments

Marco Alfo, Dankmar Boehning, and Irene Rocchetti


Efficient screening of predictive biomarkers for individual treatment selection

Shonosuke Sugasawa and Hisashi Noma


Generalized reliability based on distances

Meng Xu, Philip Reiss, and Ivor Cribben


Biometric Practice


Marginal analysis of multiple outcomes with informative cluster size

A. A. Mitani, E. K. Kaye, and K. P. Nelson


Testing tumors from different anatomic sites for clonal relatedness using somatic mutation data

Irina Ostrovnaya, Audrey Mauguen, Venkatraman E. Seshan, and Colin B. Begg


Ensemble clustering for step data via binning

Ja-Yoon Jang, Hee-Seok Oh, Yaeji Lim, and Ken Cheung


Bayesian analysis of survival data with missing censoring indicators

Naomi Brownstein, Veronica Bunn, Luis M. Castro, and Debajyoti Sinha


A Bayes factor approach with informative prior for rare genetic variant analysis from next generation sequencing data

Jingxiong Xu, Wei Xu, and Laurent Briollais


Exploiting non-systematic covariate monitoring to broaden the scope of evidence about the causal effects of adaptive treatment strategies

Noémi Kreif, Oleg Sofrygin, Julie Schmittdiel, Alyce Adams, Richard Grant, Zheng Zhu, Mark van der Laan, and Romain Neugebauer


Repeated Measures Random Forests (RMRF): Identifying factors associated with nocturnal hypoglycemia

Peter Calhoun, Richard A. Levine, and Juanjuan Fan


Improving inference for nonlinear state-space models of animal population dynamics given biased sequential life stage data

Leo Polansky, Ken B. Newman, and Lara Mitchell


A penalized structural equation modeling method accounting for secondary phenotypes for variable selection on genetically regulated expression from PrediXcan for Alzheimer’s disease

Ting-Huei Chen and Hanaa Boughal


Book review


Disease Mapping: From Foundations to Multidimensional Modeling (Miguel A. Martinez-Beneito and P. Botella-Rocamora)

Reviewed by Virgilio Gomez-Rubio


Papers to appear in future issues of Biometrics


A semi-parametric Bayesian approach to population finding with time-to-event and toxicity data in a randomized clinical trial

Satoshi Morita, Peter Mueller, and Hiroyasu Abe


Estimating and inferring the maximum degree of stimulus-locked time-varying brain connectivity networks

Kean Ming Tan, Junwei Lu, Tong Zhang, and Han Liu


Iterated multi-source exchangeability models for individualized inference with an application to mobile sensor data

Roland Brown, Yingling Fan, Kirti Das, and Julian Wolfson


Bayesian group selection in logistic regression with application to MRI data analysis

Kyoungjae Lee and Xuan Cao

Flexible link functions in a joint hierarchical Gaussian process model

Weiji Su, Xia Wang, and Rhonda D. Szczesniak


Estimating the burden of the opioid epidemic for adults and adolescents in Ohio counties

David Kline and Staci Hepler


Latent Ornstein-Uhlenbeck models for Bayesian analysis of multivariate longitudinal categorical responses

Trung Dung Tran, Emmanuel Lesaffre, Geert Verbeke, and Joke Duyck


Robust and efficient semi-supervised estimation of average treatment effects with application to electronic health records data

David Cheng, Ashwin Ananthakrishnan, and Tianxi Cai


Sensitivity analysis for subsequent treatments in confirmatory oncology clinical trials: a two-stage stochastic dynamic treatment regime approach

Yasuhiro Hagiwara, Tomohiro Shinozaki, Hirofumi Mukai, and Yutaka Matsuyama


Evaluation of longitudinal surrogate markers

Denis Agniel and Layla Parast


Quantile regression for survival data with covariates subject to detection limits

Tonghui Yu, Liming Xiang, and Huixia Judy Wang


A novel statistical method for modeling covariate effects in bisulfite sequencing derived measures of DNA methylation

Kaiqiong Zhao, Karim Oualkacha, Lajmi Lakhal-Chaieb, Aurelie Labbe, Kathleen Klein, Antonio Ciampi, Marie Hudson, and Ines Colmegna


The impact of misclassification on covariate-adaptive randomized clinical trials

Tong Wang and Wei Ma


A Bayesian hierarchical model for characterizing the diffusion of new antipsychotic drugs

Chenyang Gu, Haiden Huskamp, Julie Donohue, and Sharon-Lise Normand


Two-group Poisson-Dirichlet mixtures for multiple testing

Francesco Denti, Michele Guindani, Fabrizio Leisen, Antonio Lijoi, W. Duncan Wadsworth, and Marina Vannucci


Optimality of testing procedures for survival data in the non-proportional hazards setting

Andrea Arfe, Brian Alexander, and Lorenzo Trippa


Developing and evaluating risk prediction models with panel current status data

Stephanie Chan, Xuan Wang, Ina Jazic, Sarah Peskoe, Yingye Zheng, and Tianxi Cai


Structural factor equation models for causal network construction via directed acyclic mixed graphs

Yan Zhou, Peter X.K. Song, and Xiaoquan Wen


Batch Bayesian optimization design for optimizing a neurostimulator

Adam Kaplan and Thomas A. Murray


Semiparametric regression calibration for general hazard models in survival analysis with covariate measurement error; surprising performance under linear hazard

Ching-Yun Wang, and Xiao Song


Horvitz–Thompson-like estimation with distance-based detection probabilities for circular plot sampling of forests

Kasper Kansanen, Petteri Packalen, Matti Maltamo, and Lauri Mehtatalo


Estimating the optimal timing of surgery from observational data

Xiaofei Chen, Daniel F. Heitjan, Gerald Greil, and Haekyung Jeon-Slaughter


Spatial regression and spillover effects in cluster randomised trials with count outcomes

Karim Anaya-Izquierdo and Neal Alexander


Scalable Bayesian matrix normal graphical models for brain functional networks

Suprateek Kundu and Benjamin B. Risk


A constrained single-index regression for estimating interactions between a treatment and covariates

Hyung Park, Eva Petkova, Thaddeus Tarpey, and Todd R. Ogden


Parametric g-formula implementations for causal survival analyses

Lan Wen, Jessica G. Young, James M. Robins, and Miguel A. Hernan


A multiple robust propensity score method for longitudinal analysis with intermittent missing data

Chixiang Chen, Biyi Shen, Aiyi Liu, Rongling Wu, and Ming Wang


A Bayesian multivariate mixture model for skewed longitudinal data with intermittent missing observations: An application to infant motor development

Carter Allen, Sara E Benjamin-Neelon, and Brian Neelon


Semiparametric estimation of cross-covariance functions for multivariate random fields

Ghulam A. Qadir and Ying Sun


Resampling-based confidence intervals for model-free robust inference on optimal treatment regimes

Yunan Wu and Lan Wang


Nonparametric analysis of nonhomogeneous multi-state processes based on clustered observations

Giorgos Bakoyannis


Approximate Bayesian inference for case-crossover models

Alex Stringer, Patrick Brown, and Jamie Stafford


Estimation of incubation period and generation time based on observed length-biased epidemic cohort with censoring for COVID-19 outbreak in China

Yuhao Deng, Chong You, Yukun Liu, Jing Qin, and Xiao-Hua Zhou


Maximum likelihood abundance estimation from capture-recapture data when covariates are missing at random

Yang Liu, Yukun Liu, Pengfei Li, and Lin Zhu


Post-stratification fusion learning in longitudinal data analysis

Lu Tang and Peter Song


Analysis of noisy survival data with graphical proportional hazards measurement error model

Li-Pang Chen and Grace Y. Yi


Statistical inference for natural language processing algorithms when predicting type 2 diabetes using electronic health record notes

Brian L. Egleston, Tian Bai, Richard J. Bleicher, Taylor Stanford, Michael Lutz, and Slobodan Vucetic


Compositional knockoff filter for high-dimensional regression analysis of microbiome data

Arun Srinivasan, Lingzhou Xue, and Xiang Zhan


Variance estimation in inverse probability weighted Cox models

Di Shu, Jessica Young, Sengwee Toh, and Rui Wang


Joint Penalized Spline Modeling of Multivariate Longitudinal Data, with Application to HIV-1 RNA Load Levels and CD4 Cell Counts

Lihui Zhao, Tom Chen, Vladimir Novitsky, and Rui Wang


Tailored optimal post-treatment surveillance for cancer recurrence

Rui Chen and Menggang Yu


Bayesian compositional regression with structured priors for microbiome feature selection

Liangliang Zhang, Yushu Shi, Robert R. Jenq, Kim-Anh Do, and Christine B. Peterson


Cross-component registration for multivariate functional data, with application to growth curves

Cody Carroll, Hans-Georg Müller, and Alois Kneip


Cluster non-Gaussian functional data

Qingzhi Zhong, Huazhen Lin, and Yi Li


Ultra-high dimensional semiparametric longitudinal data analysis

Brittany Green, Heng Lian, Yan Yu, and Tianhai Zu


A weak-signal-assisted procedure for variable selection and statistical inference with an informative subsample

Fang Fang, Jiwei Zhao, S. Ejaz Ahmed, and Annie Qu


A Bayesian adaptive Phase I/II clinical trial design with late-onset competing risk outcomes

Yifei Zhang, Sha Cao, Chi Zhang, Ick Hoon Jin, and Yong Zang


Causal mediation of semicompeting risks

Yen-Tsung Huang


Discussion on "Causal mediation of semicompeting risks" by Yen-Tsung Huang

Kwun Chuen Gary Chan, Fei Gao, and Fan Xia


Discussion on "Causal mediation of semicompeting risks" by Yen-Tsung Huang

Mats J. Stensrud, Jessica G. Young, and Torben Martinussen


Discussion on "Causal mediation of semicompeting risks" by Yen-Tsung Huang

Isabel Fulcher, Ilya Shpitser, Vanessa Didelez, Kali Zhou, and Daniel O. Scharfstein


Multimodal neuroimaging data integration and pathway analysis

Yi Zhao, Lexin Li, and Brian S. Caffo


Bayesian variable selection for non-Gaussian responses: A marginally-calibrated Copula approach

Nadja Klein and Michael Stanley Smith


Covariate-driven factorization by thresholding for multi-block data

Xing Gao, Sungwon Lee, Gen Li, and Sungkyu Jung


Nonparametric trend estimation in functional time series with application to annual mortality rates

Israel Martínez-Hernández and Marc G. Genton


Regularized matrix data clustering and its application to image analysis

Xu Gao, Weining Shen, Liwen Zhang, Jianhua Hu, Norbert J. Fortin, Ron D. Frostig, and Hernando Ombao


A batch-effect adjusted Simon’s two-stage design for cancer vaccine clinical studies

Chenguang Wang, Zhixin Wang, Gary L. Rosner, Warner K. Huh, Richard B.S. Roden, and Sejong Bae


Combining primary cohort data with external aggregate information without assuming comparability

ZiqiChen, Jing Ning, Yu Shen, and Jing Qin


Post-Selection Inference for Changepoint Detection Algorithms with Application to Copy Number Variation Data

Sangwon Hyun, Kevin Z. Lin, Max G'Sell, and Ryan J. Tibshirani


Scalable and robust latent trajectory class analysis using artificial likelihood

Kari R. Hart, Teng Fei, and John J. Hanfelt


Estimation of conditional power for cluster-randomized trials with interval-censored endpoints

Kaitlyn A. Cook, and Rui Wang


Brain connectivity alteration detection via matrix-variate differential network model

Jiadong Ji, Yong He, Lei Liu, and Lei Xie


Receiver operating characteristic curves and confidence bands for support vector machines

Daniel J. Luckett, Eric B. Laber, Samer S. El-Kamary, Cheng Fan, Ravi Jhaveri, Charles M. Perou, Fatma M. Shebl, and Michael R. Kororok


Histopathological imaging-based cancer heterogeneity analysis via penalized fusion with model averaging

Baihua He, Tingyan Zhong, Jian Huang, Yanyan Liu, Qingzhao Zhang, and Shuangge Ma


A random covariance model for bi-level graphical modeling with application to resting-state fMRI data

Lin Zhang, Andrew DiLernia, Karina Quevedo, Jazmin Camchong, Kelvin Lim, and Wei Pan


Modeling excess hazard with time-to-cure as a parameter.

Olayidé Boussari, Laurent Bordes, Gaëlle Romain, Marc Colonna, Nadine Bossard, Laurent Remontet, and Valérie Jooste


Nonparametric matrix response regression with application to brain imaging data analysis

Wei Hu, Tianyu Pan, Dehan Kong, and Weining Shen


Penalized Fieller’s confidence interval for the ratio of bivariate normal means

Peng Wang, Siqi Xu, Yixin Wang, Baolin Wu, Wing Kam Fung, Guimin Gao, Zhijiang Liang, and Nianjun Liu


Semiparametric partial common principal component analysis for covariance matrices

Bingkai Wang, Xi Luo, Yi Zhao, and Brian Caffo


Semiparametric models and inference for the effect of a treatment when the outcome is nonnegative with clumping at zero

Jing Cheng and Dylan S. Small


Efficient nonparametric inference on the effects of stochastic interventions under two-phase sampling, with applications to vaccine efficacy trials

Nima S. Hejazi, Mark J. van der Laan, Holly E.Janes, Peter B. Gilbert, and David C. Benkeser


Evaluating multiple surrogate markers with censored data

Layla Parast, Tianxi Cai, and Lu Tian


A stacked approach for chained equations multiple imputation incorporating the substantive model

Lauren J. Beesley and Jeremy M. G. Taylor


A marginal moment matching approach for fitting endemic-epidemic models to underreported disease surveillance counts

Johannes Bracher and Leonhard Held


Using the “hidden” genome to improve classification of cancer types

Saptarshi Chakraborty, Colin B. Begg, and Ronglai Shen


Evaluating and improving a matched comparison of antidepressants and bone density

Ruoqi Yu


Net benefit index: assessing the influence of a biomarker for individualized treatment rules

Yiwang Zhou, Peter X.K. Song, and Haoda Fu


Poisson PCA: Poisson measurement error corrected PCA, with application to microbiome data

Toby Kenney, Hong Gu, and Tianshu Huang


Modelling sparse longitudinal data on Riemannian manifolds

Xiongtao Dai, Zhenhua Lin, and Hans-Georg Mueller


Non-parametric cluster significance testing with reference to a unimodal null distribution

Erika S. Helgeson, David M. Vock, and Eric Bair


Child mortality estimation incorporating summary birth history data

Katie Wilson and Jon Wakefield


Improving precision and power in randomized trials for COVID-19 treatments using covariate adjustment, for binary, ordinal, and time-to-event outcomes

David Benkeser, Ivan Diaz, Alex Luedtke, Jodi Segal, Daniel Scharfstein, and Michael Rosenblum


Discussion on "Improving precision and power in randomized trials for COVID-19 treatments using covariate adjustment, for binary, ordinal, and time-to-event outcomes"

Michael A. Proschan


Discussion on "Improving precision and power in randomized trials for COVID-19 treatments using covariate adjustment, for binary, ordinal, and time-to-event outcomes"

Min Zhang and Baqun Zhang


Discussion on "Improving precision and power in randomized trials for COVID-19 treatments using covariate adjustment, for binary, ordinal, and time-to-event outcomes"

Lisa M. LaVange


A class of proportional win-fractions regression models for composite outcomes

Lu Mao and Tuo Wang


A Bayesian approach to restricted latent class models for scientifically-structured clustering of multivariate binary outcomes

Zhenke Wu, Livia Casciola-Rosen, Antony Rosen, and Scott L. Zeger


A pairwise pseudo-likelihood approach for left-truncated and interval-censored data under the Cox model

Peijie Wang, Danning Li, and Jianguo Sun


Robust methods to correct for measurement error when evaluating a surrogate marker

Layla Parast, Tanya P. Garcia, Ross L. Prentice, and Raymond J. Carroll


Simultaneous variable selection and estimation for joint models of longitudinal and failure time data with interval censoring

Fengting Yi, Niansheng Tang, and Jianguo Sun


A non-parametric Bayesian model for estimating spectral densities of resting-state EEG twin data

Brian Hart, Michele Guindani, Stephen Malone, and Mark Fiecas


New multivariate tests for assessing covariate balance in matched observational studies

Hao Chen and Dylan S. Small


Identifying individual predictive factors for treatment efficacy

Ariel Alonso, Wim Van der Elst, Lizet Sanchez, Patricia Luaces, and Geert Molenberghs


Analysis of clustered interval-censored data using a class of semiparametric partly linear frailty transformation models

Chun Yin Lee, Kin Yau Wong, K. F. Lam, and Jinfeng Xu


A closed max-t test for multiple comparisons of areas under the ROC curve

Paul Blanche, Jean-Francois Dartigues, and Jeremie Riou


Speeding up Monte Carlo simulations for the adaptive sum of powered score test with importance sampling

Yangqing Deng, Yinqiu He, Gongjun Xu, and Wei Pan


Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification

Lauren J. Beesley and Bhramar Mukherjee


Joint calibrated estimation of inverse probability of treatment and censoring weights for marginal structural models

Sean Yiu and Li Su


Simultaneous spatial smoothing and outlier detection using penalized regression, with application to childhood obesity surveillance from electronic health records

Young-Geun Choi, Lawrence P. Hanrahan, Derek Norton, and Ying-Qi Zhao


Estimating the optimal individualized treatment rule from a cost-effectiveness perspective

Yizhe Xu, Tom H. Greene, Adam P. Bress, Brian C. Sauer, Brandon K. Bellows, Yue Zhang, William S. Weintraub, Andrew E. Moran, and Jincheng Shen


A latent capture history model for digital aerial surveys

D. L. Borchers, P. Nightingale, B. C. Stevenson, and R. M. Fewster


Non-linear mediation analysis with high-dimensional mediators whose causal structure is unknown

Wen Wei Loh, Beatrijs Moerkerke, Tom Loeys, and Stijn Vansteelandt


Power and sample size for observational studies of point exposure effects

Bonnie E. Shook-Sa and Michael G. Hudgens


Weight calibration to improve efficiency for estimating pure risks from the additive hazards model with the nested case-control design

Yei EunShin, Ruth M. Pfeiffer, Barry I. Graubard, and Mitchell H. Gail


Obtaining optimal cutoff values for tree classifiers using multiple biomarkers

Yuxin Zhu and Mei-Cheng Wang


Modelling group movement with behavior switching in continuous time

Mu Niu, Fay Frost, Jordan Milner, Anna Skarin, and Paul G. Blackwell


Semiparametric imputation using conditional Gaussian mixture models under item nonresponse

Danhyang Lee and Jae Kwang Kim


Two robust tools for inference about causal effects with invalid instruments

Hyunseung Kang, Youjin Lee, T. Tony Cai, and Dylan S. Small


Reader Reaction: Biased estimation with shared parameter models in the presence of competing dropout mechanisms

Edward F. Vonesh and Tom Greene


Rejoinder

Christos Thomadakis, Loukia Meligkotsidou, Nikos Pantazis, and Giota Touloumi


Restricted mean survival time as a function of restriction time

Yingchao Zhong and Douglas Earl Schaubel


Generalized multi-SNP mediation intersection-union test

Wujuan Zhong, Toni Darville, Xiaojing Zheng, Jason Fine, and Yun Li


Assuming independence in spatial latent variable models: Consequences and implications of misspecification

Francis Hui, Nicole A. Hill, and Alan Welsh


Causal Inference in high dimensions: A marriage between Bayesian modeling and good frequentist properties

Joseph Antonelli, Georgia Papadogeorgou, and Francesca Dominici


A spatial Bayesian latent factor model for image-on-image regression

Cui Guo, Jian Kang, and Timothy D. Johnson


Simultaneous confidence intervals for ranks with application to ranking institutions

Diaa Al Mohamad, Jelle Goeman, and Erik van Zwet


Bayesian group sequential enrichment designs based on adaptive regression of response and survival time on baseline biomarkers

Yeonhee Park, Suyu Liu, Peter Thall, and Ying Yuan


Synthesizing external aggregated information in the presence of population heterogeneity: A penalized empirical likelihood approach

Ying Sheng, Yifei Sun, Chiung-Yu Huang, and Mi-Ok Kim


A model for analysing clustered occurrence data

Wen-Han Hwang, Richard Huggins, and Jakub Stoklosa


Two-stage penalized regression screening to detect biomarker-treatment interactions in randomized clinical trials

Jixiong Wang, Ashish Patel, James Wason, and Paul Newcombe


Small-sample inference for cluster-based outcome-dependent sampling schemes in resource-limited settings: investigating low birthweight in Rwanda

Sara Sauer, Bethany Hedt-Gauthier, Claudia Rivera-Rodriguez, and Sebastien Haneuse


Bayesian dose-regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics

Emma Gerard, Sarah Zohar, Hoai-Thu Thai, Christelle Lorenzato, Marie-Karelle Riviere, and Moreno Ursino


Gaussian graphical model-based heterogeneity analysis via penalized fusion

Mingyang Ren, Sanguo Zhang, Qingzhao Zhang, and Shuangge Ma


Joint model for survival and multivariate sparse functional data with application to a study of Alzheimer's disease

Cai Li, Luo Xiao, and Sheng Luo


Density estimation for circular data observed with errors

Marco Di Marzio, Stefania Fensore, Agnese Panzera, and Charles Taylor


Bayesian data fusion: probabilistic sensitivity analysis for unmeasured confounding using informative priors based on secondary data

Leah Comment, Brent Coull, Corwin M. Zigler, and Linda Valeri


Information-incorporated Gaussian graphical model for gene expression data

Huangdi Yi, Qingzhao Zhang, Cunjie Lin, and Shuangge Ma


Random effects models of lymph node metastases in breast cancer: quantifying the roles of covariates and screening using a continuous growth model

Gabriel Isheden, Kamila Czene, and Keith Humphreys


Pursuing sources of heterogeneity in modeling clustered population

Yan Li, Chun Yu, Yize Zhao, Weixin Yao, Robert H. Aseltine, and Kun Chen


Causal interaction trees: Finding subgroups with heterogeneous treatment effects in observational data

Jiabei Yang, Issa J. Dahabreh, and Jon A. Steingrimsson


A kernel regression model for panel count data with nonparametric covariate functions

Yang Wang and Zhangsheng Yu


EMBRACE: an EM-based bias reduction approach through Copas-model estimation for quantifying the evidence of selective publishing in network meta-analysis

Arielle K. Marks-Anglin, Chongliang Luo, Jin Piao, Mary Beth Connolly Gibbons, Christopher Schmid, Jing Ning, and Yong Chen


Bayesian spatial homogeneity pursuit for survival data with an application to the SEER respiratory cancer data

Lijiang Geng and Guanyu Hu


Geostatistical modeling of positive definite matrices: An application to diffusion tensor imaging

Zhou Lan, Brian Reich, Joseph Guinness, Dipankar Bandyopadhyay, Liangsuo Ma, and F. Gerard Moeller


The Tukey trend test: Multiplicity adjustment using multiple marginal models

Frank Schaarschmidt, Christian Ritz, and Ludwig Hothorn


Varying coefficient frailty models with applications in single molecular experiments

Ying Hung, Li-Hsiang Lin, and C. F. Jeff Wu


Identifying regions of inhomogeneities in spatial processes via an M-RA and mixture priors

Marco H. Benedetti, Veronica J. Berrocal, and Naveen N. Narisetty


Determination and estimation of optimal quarantine duration for infectious diseases with application to data analysis of COVID-19

Ruoyu Wang and Qihua Wang


Simultaneous estimation of cluster number and feature sparsity in high-dimensional cluster analysis

Yujia Li, Xiangrui Zeng, Chien-Wei Lin, and George C. Tseng


Recruitment prediction for multi-centre clinical trials based on a hierarchical Poisson-gamma model: asymptotic analysis and improved intervals

Rachael Mountain and Chris Sherlock


Semiparametric estimation of the non-mixture cure model with auxiliary survival information

Bo Han, Ingrid Van Keilegom, and Xiaoguang Wang


Global sensitivity analysis of randomized trials with non-monotone missing binary outcomes: application to studies of substance use disorders

Daniel O. Scharfstein, Jon Steingrimsson, Aidan McDermott, Chenguang Wang, Souvik Ray, Aimee Campbell, Edward Nunes, and Abigail Matthews


Regression-based negative control of homophily in dyadic peer effect analysis

Lan Liu and Eric Tchetgen Tchetgen


Non-parametric estimation of Spearman’s rank correlation with bivariate survival data

Svetlana Eden, Chun Li, and Bryan Shepherd


A Bayesian spatial model for imaging genetics

Yin Song, Shufei Ge, Jiguo Cao, Liangliang Wang, and Farouk Salim Nathoo


Spatial factor modeling: A Bayesian matrix-normal approach for misaligned data

Lu Zhang and Sudipto Banerjee


Cox regression model under dependent truncation

Lior Rennert and Sharon X. Xie


Sparse linear discriminant analysis for multi-view structured data

Sandra E. Safo, Eun Jeong Min, and Lillian Haine


Variance reduction in the inverse probability weighted estimators for the average treatment effect using the propensity score

J. G. (Jiangang) Liao and Charles Rohde


A generalized robust allele-based genetic association test

Lin Zhang and Lei Sun


Modeling dynamic correlation in zero-inflated bivariate count data with applications to single-cell RNA sequencing data

Zhen Yang and Yen-Yi Ho


Distributional independent component analysis for diverse neuroimaging modalities

Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo


Inverse probability weighted estimators of vaccine effects accommodating partial interference and censoring

Sujatro Chakladar, Samuel P. Rosin, Michael G. Hudgens, M. Elizabeth Halloran, John D. Clemens, Mohammad Ali, and Michael E. Emch,


Integrative analysis of multiple case-control studies

Han Zhang, Lu Deng, William Wheeler, Jing Qin, and Kai Yu


On polygenic risk scores for complex traits prediction

Bingxin Zhao and Fei Zou


Restricted function-on-function linear regression model

Ruiyan Luo and Xin Qi


A transformation-free linear regression for compositional outcomes and predictors

Jacob Fiksel, Scott L. Zeger, and Abhirup Datta


Inferring UK COVID-19 fatal infection trajectories from daily mortality data: were infections already in decline before the UK lockdowns?

Simon N. Wood


Testing for association in multi-view network data

Lucy L. Gao, Daniela Witten, and Jacob Bien


Parameter inference for a stochastic kinetic model of expanded polyglutamine proteins

H. F. Fisher, R. J. Boys, C. S. Gillespie, C. J. Proctor, and A. Golightly


Multivariate survival analysis in big data: a divide-and-combine approach

Wei Wang, Shou-En Lu, Jerry Q. Cheng, Minge Xie, and John B. Kostis


Bayesian analysis of coupled cellular and nuclear trajectories for cell migration

Saptarshi Chakraborty, Tian Lan, Yiider Tseng, and Samuel W.K. Wong


A consistent version of distance covariance for right-censored survival data and its application in hypothesis testing

Dominic Edelmann, Thomas Welchowski, Axel Benner


Stratified Cox models with time-varying effects for national kidney transplant patients: A new block-wise steepest ascent method

Kevin He, Ji Zhu, Jian Kang, and Yi Li


Semiparametric analysis of clustered interval-censored survival data using Soft Bayesian Additive Regression Trees (SBART)

Piyali Basak, Antonio Ricardo Linero, Debajyoti Sinha, and Stuart R. Lipsitz


Optimization of sampling designs for pedigrees and association studies

Olivier David, Arnaud Le Rouzic, and Christine Dillmann


Feature screening with large scale and high dimensional survival data

Grace Yi, Wenqing He, and Raymond J. Carroll


Regression with interval-censored covariates: application to cross-sectional incidence estimation

Doug Morrison, Oliver Laeyendecker, and Ron Brookmeyer


Efficient detection and classification of epigenomic changes under multiple conditions

Pedro L. Baldoni, Naim U. Rashid, and Joseph G. Ibrahim


Quantifying direct and indirect effect for longitudinal mediator and survival outcome using joint modeling approach

Cheng Zheng and Lei Liu


Spatial+: a novel approach to spatial confounding

Emiko Dupont, Simon N. Wood, and Nicole H. Augustin


Semiparametric estimation of structural nested mean models with irregularly spaced longitudinal observations

Shu Yang


Estimating vaccine efficacy over time after a randomized study is unblinded

Anastasios A. Tsiatis and Marie Davidian


Modeling semi-competing risks data as a longitudinal bivariate process

Daniel Nevo, Deborah Blacker, Eric B. Larson, and Sebastien Haneuse


Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data

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