Papers to Appear


Cover Image:  Human Leukocyte Antigen (HLA) alleles are genetic variants of HLA genes. The three HLA class I (HLA-I) genes (HLA-A, HLA-B, and HLA-C) encode for thousands of HLA-I alleles in the human population. An important function of these HLA-I alleles is to present peptides within a cell at cell surface, which is a key step in our immune system. This figure represents the hierarchical clustering of 130 HLA-I alleles, where the distance between two alleles is smaller if they present a similar set of peptides. This clustering result demonstrates that HLA-I alleles that present similar sets of peptides have similar DNA sequences, as reflected by their names. This comes from Figure 2C in the article authored by Laura Y. Zhou, Fei Zou, and Wei Sun, and entitled "Prioritizing candidate peptides for cancer vaccines through predicting peptide presentation by HLA-I proteins."



Biometric Methodology


Structural cumulative survival models for estimation of treatment effects accounting for treatment switching in randomized experiments

Andrew Ying and Eric J. Tchetgen Tchetgen


Dimension reduction for integrative survival analysis

Aaron J. Molstad and Rohit K. Patra


Concordance indices with left-truncated and right-censored data

Nicholas Hartman, Sehee Kim, Kevin He, and John D. Kalbfleisch


Joint inference for competing risks data using multiple endpoints

Jiyang Wen, Chen Hu, and Mei-Cheng Wang


Maximum likelihood estimation in the additive hazards model

Chengyuan Lu, Jelle Goeman, and Hein Putter


Penalized estimation of frailty-based illness-death models for semi-competing risks

Harrison T. Reeder, Junwei Lu, and Sebastien J. Haneuse


Marginal proportional hazards models for clustered interval-censored data with time-dependent covariates

Kaitlyn Cook, Wenbin Lu, and Rui Wang


Improved semiparametric estimation of the proportional rate model with recurrent event data

Ming-Yueh Huang and Chiung-Yu Huang


Non-parametric estimation of the age-at-onset distribution from a cross-sectional sample

Soutrik Mandal, Jing Qin, and Ruth M. Pfeiffer


An information ratio based goodness-of-fit test for copula models on censored data

Tao Sun, Yu Cheng, and Ying Ding


Model uncertainty quantification in Cox regression

Gonzalo Garcia-Donato, Stefano Cabras, and Maria Eugenia Castellanos


General independent censoring in event-driven trials with staggered entry

Jasmin Ruhl, Jan Beyersmann, and Sarah Friedrich


Nonparametric inference of general while-alive estimands for recurrent events

Lu Mao


Two-level Bayesian interaction analysis for survival data incorporating pathway information

Xing Qin, Shuangge Ma, and Mengyun Wu


A Bayesian multivariate mixture model for high throughput spatial transcriptomics

Carter Allen, Yuzhou Chang, Brian Neelon, Won Chang, Hang J. Kim, Zihai Li, Qin Ma, and Dongjun Chung


Tractable Bayes of skew-elliptical link models for correlated binary data

Zhongwei Zhang, Reinaldo B. Arellano-Valle, Marc G. Genton, and Raphael Huser


Integrative Bayesian models using post-selective inference: a case study in radiogenomics

Snigdha Panigrahi, Shariq Mohammed, Arvind Rao, and Veerabhadran Baladandayuthapani


Bayesian regression analysis of skewed tensor responses

Inkoo Lee, Debajyoti Sinha, Qing Mai, Xin Zhang, and Dipankar Bandyopadhyay


Adaptive Bayesian sum of trees model for covariate dependent spectral analysis

Yakun Wang, Zeda Li, and Scott A. Bruce


Solutions for surrogacy validation with longitudinal outcomes for a gene therapy

Emily K. Roberts, Michael R. Elliott, and Jeremy M. G. Taylor


Subset selection for linear mixed models

Daniel R. Kowal


Grouped generalized estimating equations for longitudinal data analysis

Tsubasa Ito and Shonosuke Sugasawa


Asynchronous functional linear regression models for longitudinal data in reproducing kernel Hilbert space

Ting Li, Huichen Zhu, Tengfei Li, and Hongtu Zhu


Contrasting principal stratum and hypothetical strategy estimands in multi-period crossover trials with incomplete data

John N.S. Matthews, Sofia Bazakou, Robin Henderson, and Linda D. Sharples


Optimal multiple testing and design in clinical trials

Ruth Heller, Abba Krieger, and Saharon Rosset


Change-plane analysis for subgroup detection with a continuous treatment

Peng Jin, Wenbin Lu, Yu Chen, and Mengling Liu


Efficient targeted learning of heterogeneous treatment effects for multiple subgroups

Waverly Wei, Maya Petersen, Mark J. van der Laan, Zeyu Zheng, Chong Wu, and Jingshen Wang


Tensor response quantile regression with neuroimaging data

Bo Wei, Limin Peng, Ying Guo, Amita Manatunga, and Jennifer Stevens


Joint semiparametric models for case-cohort designs

Weibin Zhong and Guoqing Diao


Multidimensional adaptive P-splines with application to Neurons’ activity studies

Maria Xose Rodriguez-Alvarez, Maria Durban, Paul H. C. Eilers, Dae-Jin Lee, and Francisco Gonzalez


Combining parametric and nonparametric models to estimate treatment effects in observational studies

Daniel Daly-Grafstein and Paul Gustafson


Semiparametric estimation of the transformation model by leveraging external aggregate data in the presence of population heterogeneity

Yu-Jen Cheng, Yen-Chun Liu, Chang-Yu Tsai, and Chiung-Yu Huang


A semiparametric joint model for cluster size and subunit-specific interval-censored outcomes

Chun Yin Lee, Kin Yau Wong, K. F. Lam, and Dipankar Bandyopadhyay


A robust approach for electronic health record-based case-control studies with contaminated case pools

Guorong Dai, Yanyuan Ma, Jill Schnall, Jinbo Chen, and Raymond J. Carroll


Quantile regression for nonignorable missing data with its application of analyzing electronic medical records

Aiai Yu, Yujie Zhong, Xingdong Feng, and Ying Wei


Frequentist model averaging for undirected Gaussian graphical models

Huihang Liu and Xinyu Zhang


Nonparametric scanning tests of homogeneity for hierarchical models with continuous covariates

David Todem, Wei-Wen Hsu, and KyungMann Kim


Identifying alert concentrations using a model-based bootstrap approach

Kathrin Möllenhoff, Kirsten Schorning, and Franziska Kappenberg


Adjusting for publication bias in meta-analysis via inverse probability weighting using clinical trial registries

Ao Huang, Kosuke Morikawa, Tim Friede, and Satoshi Hattori


Elastic analysis of irregularly or sparsely sampled curves

Lisa Steyer, Almond Stocker, and Sonja Greven


A general framework for subgroup detection via one-step value difference estimation

Dana Johnson, Wenbin Lu, and Marie Davidian


Pair-switching rerandomization

Ke Zhu and Hanzhong Liu


Double reduction estimation and equilibrium tests in natural autopolyploid populations

David Gerard 


Centre-augmented $\ell_2$-type regularization for subgroup learning

Ling Zhou, Ye He, Yingcun Xia, and Huazhen Lin


A general modelling framework for open wildlife populations based on the Polya Tree prior

Alex Diana, Eleni Matechou, Jim Griffin, Todd Arnold, Simone Tenan, and Stefano Volponi


A novel penalized inverse-variance weighted estimator for Mendelian randomization with applications to COVID-19 outcomes

Siqi Xu, Peng Wang, Wing Kam Fung, and Zhonghua Liu


Testing weak nulls in matched observational studies

Colin B. Fogarty


Mendelian randomization mixed-scale treatment effect robust identification and estimation for causal inference

Zhonghua Liu, Ting Ye, Baoluo Sun, Mary Schooling, and Eric Tchetgen Tchetgen


Generalized propensity score approach to causal inference with spatial interference

A. Giffin, B. J. Reich, S. Yang, and A. G. Rappold


Functional data analysis with covariate-dependent mean and covariance structures

Chenlin Zhang, Huazhen Lin, Li Liu, Jin Liu, and Yi Li


Simultaneous cluster structure learning and estimation of heterogeneous graphs for matrix-variate fMRI data

Dong Liu, Changwei Zhao, Yong He, Lei Liu, Ying Guo, and Xinsheng Zhang


Estimating tree-based dynamic treatment regimes using observational data with restricted treatment sequences

Nina Zhou, Lu Wang, and Daniel Almirall


Segmented correspondence curve regression for quantifying covariate effects on the reproducibility of high-throughput experiments

Feipeng Zhang and Qunhua Li


Concave likelihood-based regression with finite-support response variables

K. O. Ekvall and M. Bottai


Boosting distributional copula regression

Nicolai Hans, Nadja Klein, Florian Faschingbauer, Michael Schneider, and Andreas Mayr 


On generalized latent factor modeling and inference for high-dimensional binomial data

Ting Fung Ma, Fangfang Wang, and Jun Zhu


Microbiome subcommunity learning with logistic-tree normal latent Dirichlet allocation

Patrick LeBlanc and Li Ma


Identifying brain hierarchical structures associated with Alzheimer’s disease

Yi Zhao, Bingkai Wang, Chin-Fu Liu, Andreia V. Faria, Michael I. Miller, Brian S. Caffo, and Xi Luo 


How well can Fine Balance work for covariate balancing

Ruoqi Yu


CEDAR: Communication Efficient Distributed Analysis for Regressions

C. Chang, Z. Bu, and Q. Long


Statistical inference and power analysis for direct and spillover effects in two-stage randomized experiments

Zhichao Jiang, Kosuke Imai, and Anup Malani


Estimating the area under the ROC curve when transporting a prediction model to a target population

Bing Li, Constantine Gatsonis, Issa J. Dahabreh, and Jon A. Steingrimsson


Inference for the dimension of a regression relationship using pseudo-covariates

Shih-Hao Huang, Kerby Shedden, and Hsin-wen Chang


Consistent estimation of the number of communities via regularized network embedding

Mingyang Ren, Sanguo Zhang, and Junhui Wang


Biometric Practice


Automated analysis of low-field brain MRI in cerebral malaria

Danni Tu, Manu S. Goyal, Jordan D. Dworkin, Samuel Kampondeni, Lorenna Vidal, Eric Biondo-Savin, Sandeep Juvvadi, Prashant Raghavan, Jennifer Nicholas, Karen Chetcuti, Kelly Clark, Timothy Robert-Fitzgerald, Theodore D. Satterthwaite, Paul Yushkevich, Christos Davatzikos, Guray Erus, Nicholas J. Tustison, Douglas G. Postels, Terrie E. Taylor, Dylan S. Small, and Russell T. Shinohara


A high-dimensional mediation model for a neuroimaging mediator: integrating clinical, neuroimaging, and neurocognitive data to mitigate late effects in pediatric cancer

Xiaoqing Jade Wang, Yimei Li, Wilburn E. Reddick, Heather M. Conklin, John O. Glass, Arzu Onar-Thomas, Amar Gajjar, Cheng Cheng, and Zhao-Hua Lu


A latent state space model for estimating brain dynamics from electroencephalogram (EEG) data

Qinxia Wang, Ji Loh, Xiaofu He, and Yuanjia Wang


Bayesian treatment screening and selection using subgroup-specific utilities of response and toxicity

Juhee Lee, Peter F. Thall, and Pavlos Msaouel


Bayesian hierarchical quantile regression with application to characterizing the immune architecture of lung cancer

Priyam Das, Christine B. Peterson, Yang Ni, Alexandre Reuben, Jiexin Zhang, Jianjun Zhang, Kim-Anh Do, and Veerabhadran Baladandayuthapani


Bayesian sample size calculations for comparing two strategies in SMART studies

Armando Turchetta, Erica E. M. Moodie, David A. Stephens, and Sylvie D. Lambert


Fast Bayesian inference for large occupancy dataset

Alex Diana, Emily B. Dennis, Eleni Matechou, and Byron J.T. Morgan


Comparing COVID-19 incidences longitudinally per economic sector against the background of preventive measures and vaccination

Florian Stijven, Johan Verbeeck, and Geert Molenberghs


Age-related model for estimating the symptomatic and asymptomatic transmissibility of COVID-19 patient

Jianbin Tan, Ye Shen, Yang Ge, Leonardo Martinez, and Hui Huang 


Correcting delayed reporting of COVID-19 using the Generalized-Dirichlet-Multinomial method

Oliver Stoner, Alba Halliday, and Theo Economou


Assessing exposure-time treatment effect heterogeneity in stepped wedge cluster randomized trials

Lara Maleyeff, Fan Li, Sebastien Haneuse, and Rui Wang


Design considerations for two stage enrichment clinical trials

Rosamarie Frieri, William F. Rosenberger, Nancy Flournoy, and Zhantao Lin


Efficient and robust approaches for analysis of SMARTs: illustration using the ADAPT-R trial

Lina Montoya, Michael Kosorok, Elvin Geng, Joshua Schwab, Thomas Odeny, and Maya Petersen


Infinite hidden Markov models for multiple multivariate time series with missing data

Lauren Hoskovec, Matthew D. Koslovsky, Kirsten Koehler, Nicholas Good, Jennifer L. Peel, John Volckens, and Ander Wilson


Spatial dependence modeling of latent susceptibility and time to joint damage in psoriatic arthritis

Fangya Mao and Richard J. Cook


Semiparametric distributed lag quantile regression for modeling time-dependent exposure mixtures

Yuyan Wang, Akhgar Ghassabian, Bo Gu, Yelena Afnansyeva, Yiwei Li, Leonardo Trasande, and Mengling Liu


Misdiagnosis-related harm quantification through mixture models and harm measures

Yuxin Zhu, Zheyu Wang, and David Newman-Toker


Multi-wave validation sampling for error-prone electronic health records

Bryan E. Shepherd, Kyunghee Han, Tong Chen, Aihua Bian, Shannon Pugh, Stephany N. Duda, Thomas Lumley, William J. Heerman, and Pamela A. Shaw


Prioritizing candidate peptides for cancer vaccines through predicting peptide presentation by HLA-I proteins

Laura Y. Zhou, Fei Zou, and Wei Sun


Neural network on interval censored data with application to the prediction of Alzheimer’s Disease

Tao Sun and Ying Ding


Delivering spatially comparable inference on the risks of multiple severities of respiratory disease from spatially misaligned disease count data

Duncan Lee and Craig Anderson


Associating somatic mutation with clinical outcomes through kernel regression and optimal transport

Paul Little, Li Hsu, and Wei Sun


Pattern-based clustering of daily weigh-in trajectories using dynamic time warping

Samantha Bothwell, Alex Kaizer, Ryan Peterson, Danielle Ostendorf, Victoria Catenacci, and Julia Wrobel


Latent multinomial models for extended batch mark data

Wei Zhang, Simon Bonner, and Rachel McCrea


A sensitivity analysis approach for the causal hazard ratio in randomized and observational studies

Rachel Axelrod and Daniel Nevo


Hospital profiling using Bayesian decision theory

Johannes Hengelbrock, Johannes Rauh, Jona Cederbaum, Maximilian Kähler, and Michael Höhle


Book Reviews


Probability and Random Variables: Theory and Applications (Iickho Song, So Ryoung Park, and Seokho Yoon)

Reviewed by Chen-Po Liao


Mendelian Randomization (Stephen Burgess and Simon G. Thompson)

Reviewed by Chia Yen Chen


Fundamentals of High-Dimensional Statistics: With Exercises and R Labs (Johannes Lederer)

Reviewed by Li-Pang Chen




Papers to appear in future issues of Biometrics


Optimal test procedures for multiple hypotheses controlling the familywise expected loss

Willi Maurer, Frank Bretz, and Xiaolei Xun

Discussion on "Optimal test procedures for multiple hypotheses controlling the familywise expected loss" by Willi Maurer, Frank Bretz, and Xiaolei Xun

Yoav Benjamini, Ruth Heller, Abba Krieger, Saharon Rosset


Discussion on "Optimal test procedures for multiple hypotheses controlling the familywise expected loss" by Willi Maurer, Frank Bretz, and Xiaolei Xun

Sudipto Banerjee


Discussion on "Optimal test procedures for multiple hypotheses controlling the familywise expected loss" by Willi Maurer, Frank Bretz, and Xiaolei Xun

Lisa M. LaVange, Ethan M. Alt, and Joseph G. Ibrahim


Discussion on "Optimal test procedures for multiple hypotheses controlling the familywise expected loss" by Willi Maurer, Frank Bretz, and Xiaolei Xun

Werner Brannath


Rejoinder to discussions on "Optimal test procedures for multiple hypotheses controlling the familywise expected loss"

Willi Maurer, Frank Bretz, and Xiaolei Xun


The central role of the identifying assumption in population size estimation

Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield


Discussion on "The central role of the identifying assumption in population size estimation" by Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield

John Whitehead


Discussion on "The central role of the identifying assumption in population size estimation" by Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield

Li-Chun Zhang


Discussion on "The central role of the identifying assumption in population size estimation" by Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield

Ruth King, Rachel McCrea, and Antony Overstall


Discussion on "The central role of the identifying assumption in population size estimation" by Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield

Daniel Manrique-Vallier


Rejoinder to discussions on "The central role of the identifying assumption in population size estimation" 

Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield


Spatially adaptive calibrations of AirBox PM2.5 data

Hsin-Cheng Huang


Additive subdistribution hazards regression for competing risks data in case-cohort studies

Adane F. Wogu, Haolin Li, Shanshan Zhao, Hazel B. Nichols, and Jianwen Cai


Stabilized direct learning for efficient estimation of individualized treatment rules

Kushal S. Shah, Haoda Fu, and Michael R. Kosorok


Bayesian design of multi-regional clinical trials with time-to-event endpoints

Nathan W. Bean, Joseph G. Ibrahim, and Matthew A. Psioda


Relative contrast estimation and inference for treatment recommendation

Muxuan Liang and Menggang Yu


Competition-based control of the false discovery proportion

Dong Luo, Arya Ebadi, Kristen Emery, Yilun He, William Stafford Noble, and Uri Keich


Optimal sampling for positive only electronic health record data

Seong-ho Lee, Yanyuan Ma, Ying Wei, and Jinbo Chen


Combining observational and experimental datasets using shrinkage estimators

Evan T. R. Rosenman, Guillaume Basse, Art B. Owen, and Mike Baiocchi


Bayesian inference for a principal stratum estimand on recurrent events truncated by death

Tianmeng Lyu, Bjorn Bornkamp, Guenther Mueller-Velten, and Heinz Schmidli


Entropy balancing for causal generalization with target sample summary information

Rui Chen, Guanhua Chen, and Menggang Yu


A seasonality-adjusted sequential test for vaccine safety surveillance

Rex Shen, Keran Moll, Ying Lu, and Lu Tian


Estimating population size: the importance of model and estimator choice

Matthew R. Schofield, Richard J. Barker, William A. Link, and Heloise Pavanato


Latent trajectory models for spatio-temporal dynamics in Alaskan ecosystems

Xinyi Lu, Mevin B. Hooten, Ann M. Raiho, David K. Swanson, Carl A. Roland, and Sarah E. Stehn


Bayesian nonparametric adjustment of confounding

Chanmin Kim, Maucicio Tec, and Corwin Zigler


Nonlinear function-on-scalar regression via functional universal approximation

Ruiyan Luo and Xin Qi


Homogeneity tests of covariance for high-dimensional functional data with applications to event segmentation

Ping-Shou Zhong


DROID: Dose-ranging approach to optimizing dose in oncology drug development

Beibei Guo and Ying Yuan


Analyzing data in complicated 3D domains: smoothing, semiparametric regression and functional principal component analysis

Eleonora Arnone, Luca Negri, Ferruccio Panzica, and Laura M. Sangalli


Improved inference for doubly robust estimators of heterogeneous treatment effects

Heejun Shin and Joseph Antonelli


Spatial modeling of M. tuberculosis transmission with dyadic genetic relatedness data

Joshua L. Warren, Melanie H. Chitwood, Benjamin Sobkowiak, Caroline Colijn, and Ted Cohen


A nonparametric test of group distributional differences for hierarchically-clustered functional data

Alexander S. Long, Brian J. Reich, Ana-Maria Staicu, and John Meitzen


Individualized causal discovery with latent trajectory embedded Bayesian networks

Fangting Zhou, Kejun He, and Yang Ni


Finding influential subjects in a network using a causal framework

Youjin Lee, Ashley Buchanan, Elizabeth Ogburn, Samuel R. Friedman, M. Elizabeth Halloran, Natallia V. Katenka, Jing Wu, and Georgios Nikolopoulos


Modelling Covid-19 contact-tracing using the ratio regression capture-recapture approach

D. Böhning,  R. Lerdsuwansri, and P. Sangnawakij


Latent deformation models for multivariate functional data and time warping separability

Cody Carroll and Hans-Georg Mueller


Covariate-adjusted response-adaptive designs based on semiparametric approaches

Hai Zhu and Hongjian Zhu


Efficient and flexible estimation of natural direct and indirect effects under intermediate confounding and monotonicity constraints

Kara E. Rudolph, Nicholas Williams, and Ivan Diaz


Causal mediation analysis using image mediator bounded in irregular domain with an application to breast cancer

Shu Jiang and Graham A. Colditz


FDR controlled multiple testing for union null hypotheses: A knockoff-based approach

Ran Dai and Cheng Zheng


Nonparametric failure time: time-to-event machine learning with heteroskedastic Bayesian additive regression trees and low information omnibus Dirichlet process mixtures

R.A. Sparapani, B.R. Logan, M.J. Maiers, P.W. Laud, and R.E. McCulloch


Estimation of time-specific intervention effects on continuously distributed time-to-event outcomes by targeted maximum likelihood estimation

Helene C. W. Rytgaard, Frank Eriksson, and Mark J. van der Laan


A Bayesian zero-inflated Dirichlet-multinomial regression model for multivariate compositional count data

Matthew D. Koslovsky


A synthetic data integration framework to leverage external summary-level information from heterogeneous populations

Tian Gu, Jeremy M.G. Taylor, and Bhramar Mukherjee


Interim monitoring of sequential multiple assignment randomized trials using partial information

Cole Manschot, Eric Laber, and Marie Davidian


Longitudinal incremental propensity score interventions for limited resource settings

Aaron Sarvet, Kerollos N. Wanis, Jessica Young, Roberto Hernandez-Alejandro, and Mats J. Stensrud


Information criteria for detecting change-points in the Cox proportional hazards model

Ryoto Ozaki, and Yoshiyuki Ninomiya 


An efficient data integration scheme for synthesizing information from multiple secondary datasets for the parameter inference of the main analysis

Chixiang Chen, Ming Wang, and Shuo Chen


Supervised convex clustering

Minjie Wang, Tianyi Yao, and Genevera I. Allen


Detecting the spatial clustering of exposure-response relationships with estimation error: a novel spatial scan statistic

Wei Wang, Sheng Li, Tao Zhang, Fei Yin, and Yue Ma


Asynchronous and error-prone longitudinal data analysis via functional calibration

Xinyue Chang, Yehua Li, and Yi Li


Combining mixed effects hidden Markov models with latent alternating recurrent event processes to model diurnal active-rest cycles

Benny Ren and Ian Barnett


Identifying and estimating effects of sustained interventions under parallel trends assumptions

Audrey Renson, Michael G. Hudgens, Alexander P. Keil, Paul N. Zivich, and Allison E. Aiello


Conditional cross-design synthesis estimators for generalizability in Medicaid

Irina Degtiar, Tim Layton, Jacob Wallace, and Sherri Rose


Estimating optimal individualized treatment rules with multistate processes

Giorgos Bakoyannis


Sparse Bayesian modeling of hierarchical independent component analysis: reliable estimation of individual differences in brain networks

Joshua Lukemire, Giuseppe Pagnoni, and Ying Guo


Sparse estimation in semi-parametric finite mixture of varying coefficient regression models

Abbas Khalili, Farhad Shokoohi, Masoud Asgharian, and Shili Lin


Imputation-based Q-learning for optimizing dynamic treatment regimes with right-censored survival outcome

Lingyun Lyu, Yu Cheng, and Abdus S. Wahed


Bi-level structured functional analysis for genome-wide association studies

Mengyun Wu, Fan Wang, Yeheng Ge, Shuangge Ma, and Yang Li


On interquantile smoothness of censored quantile regression with induced smoothing (CQRIS)

Zexi Cai and Tony Sit


An accelerated failure time regression model for illness-death data: A frailty approach

Lea Kats and Malka Gorfine


A case study of glucose levels during sleep using multilevel fast function on scalar regression inference

Renat Sergazinov, Andrew Leroux, Erjia Cui, Ciprian Crainiceanu, R. Nisha Aurora, Naresh M. Punjabi, and Irina Gaynanova


Pathological imaging-assisted cancer gene-environment interaction analysis

Kuangnan Fang, Jingmao Li, Qingzhao Zhang, Yaqing Xu, and Shuangge Ma


Correcting for bias due to mismeasured exposure history in longitudinal studies with continuous outcomes

Jiachen Cai, Ning Zhang, Xin Zhou, Donna Spiegelman, and Molin Wang


Group variable selection for Cox model with interval-censored failure time data

Yuxiang Wu, Hui Zhao, and Jianguo Sun


Instability of inverse probability weighting methods and a remedy for non-ignorable missing data

Pengfei Li, Jing Qin, and Yukun Liu 


Bayesian functional data analysis over dependent regions and its application for identification of differentially methylated regions

Suvo Chatterjee, Shrabanti Chowdhury, Duchwan Ryu, and Sanjib Basu


Hierarchical nuclear norm penalization for multi-view data integration

Sangyoon Yi, Raymond K. W. Wong, and Irina Gaynanova


Flexible joint modeling of mean and dispersion for the directional tuning of neuronal spike counts

Maria Alonso-Pena, Irene Gijbels, and Rosa M. Crujeiras


A double robust test for high-dimensional gene co-expression networks conditioning on clinical information

Maomao Ding, Ruosha Li, Jin Qin, and Jing Ning


Prior and posterior checking of implicit causal assumptions

Antonio R. Linero


Constructing time-invariant dynamic surveillance rules for optimal monitoring schedules

Xinyuan Dong, Yingye Zheng, Daniel W. Lin, Lisa Newcomb, and Ying-Qi Zhao


Dirichlet process mixture models for the analysis of repeated attempt designs

M.J. Daniels, M. Lee, and W. Feng


Conditional inference in cis-Mendelian randomization using weak genetic factors

Ashish Patel, Dipender Gill, Paul Newcombe, and Stephen Burgess


A stochastic block Ising model for multi-layer networks with inter-layer dependence

Jingnan Zhang, Chengye Li, and Junhui Wang 


Dynamic enrichment of Bayesian small sample, sequential, multiple assignment randomized trial (snSMART) design using natural history data: A case study from Duchenne muscular dystrophy

Sidi Wang,  Kelley M. Kidwell, and Satrajit Roychoudhury


Ensuring valid inference for Cox hazard ratios after variable selection

Kelly Van Lancker, Oliver Dukes, and Stijn Vansteelandt


A semiparametric Cox-Aalen transformation model with censored data

Xi Ning, Yinghao Pan, Yanqing Sun, and Peter B. Gilbert


Analysis of dynamic restricted mean survival time based on pseudo-observations

Zijing Yang, Chengfeng Zhang, Yawen Hou, and Zheng Chen


Generating designs for comparative experiments with two blocking factors

Nha Vo-Thanh and Hans-Peter Piepho


Simultaneous selection and inference for varying coefficients with zero regions: A soft-thresholding approach

Yuan Yang, Ziyang Pan, Jian Kang, Chad Brummett, and Yi Li


Bayesian model selection for generalized linear mixed models

Shuangshuang Xu, Marco A. R. Ferreira, Erica M. Porter, and Christopher T. Franck


Sample size & power determination for multiparameter evaluation in nonlinear regression models with potential stratification

Michael J. Martens, Soyoung Kim, and Kwang Woo Ahn


Transportability of causal inference under random dynamic treatment regimes for kidney-pancreas transplantation

Grace R. Lyden, David M. Vock, Erika S. Helgeson, Erik B. Finger, Arthur J. Matas, and Jon J. Snyder


Analysis of length-biased and partly interval-censored survival data with mismeasured covariates

Li-Pang Chen and Bangxu Qiu


Analyzing clustered continuous response variables with ordinal regression models

Yuqi Tian, Bryan E. Shepherd, Chun Li, Donglin Zeng, and Jonathan J. Schildcrout


Explaining transmission rate variations and forecasting epidemic spread in multiple regions with a semiparametric mixed effects SIR model

David A. Buch, James Johndrow, and David B. Dunson


Melding wildlife surveys to improve conservation inference

Justin J. Van Ee, Christian A. Hagen, David C. Pavlacky Jr., Kent A. Fricke, Matthew D. Koslovsky, and Mevin B. Hooten


Optimizing treatment allocation in randomized clinical trials by leveraging baseline covariates

Wei Zhang, Zhiwei Zhang, and Aiyi Liu


A self-censoring model for multivariate nonignorable nonmonotone missing data

Yilin Li, Wang Miao, Ilya Shpitser, and Eric J. Tchetgen Tchetgen


Nonlinear multilevel joint model for individual lesion kinetics and survival to characterize intra-individual heterogeneity in patients with advanced cancer

Marion Kerioui, Maxime Beaulieu, Solène Desmée, Julie Bertrand, François Mercier, Jin Y. Jin, René Bruno, and Jérémie Guedj


A proportional incidence rate model for aggregated data to study the vaccine effectiveness against COVID-19 hospital and ICU admissions

Ping Yan, Muhammad Abu Shadeque Mullah, and Ashleigh Tuite 


A Bayesian causal inference approach in observational studies with missingness in covariates and outcomes

Huaiyu Zang, Hang J. Kim, Bin Huang, and Rhonda Szczesniak


A second evidence factor for a second control group

Paul R. Rosenbaum


Efficient algorithms for building representative matched pairs with enhanced generalizability

Bo Zhang


How to analyze continuous and discrete repeated measures in small sample cross-over trials?

Johan Verbeeck, Martin Geroldinger, Konstantin Thiel, Andrew C. Hooker, Sebastian Ueckert, Mats Karlsson, Arne C. Bathke, Johann W. Bauer, Geert Molenberghs, and Georg Zimmermann


SAM: Self-adapting mixture prior to dynamically borrow information from historical data in clinical trials

Peng Yang, Yuansong Zhao, Lei Nie, Jonathon Vallejo, and Ying Yuan 


Multiresolution categorical regression for interpretable cell type annotation

Aaron J. Molstad and Motwani Keshav


Bayesian meta-analysis of penetrance for cancer risk

Thanthirige Ruberu, Danielle Lakshika Braun, Giovanni Parmigiani, and Swati Biswas


Functional Bayesian networks for discovering causality from multivariate functional data

Fangting Zhou, Kejun He, Kunbo Wang, Yanxun Xu, and Yang Ni


Study design for restricted mean time analysis of recurrent events and death

Lu Mao


Latent factor model for multivariate functional data

Ruonan Li, and Luo Xiao


Regression-based multiple treatment effect estimation under covariate-adaptive randomization

Yujia Gu, Hanzhong Liu, and Wei Ma


Personalized treatment selection via product partition models with covariates

Matteo Pedone, Raffaele Argiento, and Francesco C. Stingo


Multiple augmented reduced rank regression for pan-cancer analysis

Jiuzhou Wang and Eric F. Lock


Longitudinal varying coefficient single-index model with censored covariates

Shikun Wang, Jing Ning, Ying Xu, Tina Ya-Chen Shih, Yu Shen, and Liang Li


Incorporating participants’ welfare into sequential multiple assignment randomized trials

Xinru Wang, Nina Deliu, Yusuke Narita, and Bibhas Chakraborty


Homogeneity pursuit and variable selection in regression models for multivariate abundance data

Francis K.C. Hui, Luca Maestrini, and Alan H. Welsh