Papers to Appear
Report of the Editors - 2023
Biometric Methodology
Discussion Paper
The central role of the identifying assumption in population size estimation
Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield
Discussion
Ruth King, Rachel McCrea, and Antony Overstall
Discussion
John Whitehead
Discussion
Daniel Manrique-Vallier
Discussion
Li-Chun Zhang
Rejoinder
Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield
Conditional modeling of panel count data with partly interval-censored failure event
Xiangbin Hu, Wen Su, Zhi-Sheng Ye, and Xingqiu Zhao
Fitting the Cox proportional hazards model to big data
Jianqiao Wang, Donglin Zeng, and D. Y. Lin
Efficient computation of high-dimensional penalized generalized linear mixed models by latent factor modeling of the random effects
Hillary M. Heiling, Naim U. Rashid, Quefeng Li, Xianlu L. Peng, Jen Jen Yeh, and Joseph G. Ibrahim
Asymptotic uncertainty of false discovery proportion
Meng Mei, Tao Yu, and Yuan Jiang
Bias correction models for electronic health records data in the presence of non-random sampling
Jiyu Kim, Rebecca Anthopolos, Judy Zhong
Accounting for network noise in graph-guided Bayesian modeling of structured high-dimensional data
Wenrui Li, Changgee Chang, Suprateek Kundu, and Qi Long
Changing interim monitoring in response to internal clinical trial data
Michael A. Proschan, Martha Nason, Ana M Ortega-Villa, and Jing Wang
Diagnostics for regression models with semicontinuous outcomes
Lu Yang
A boosting method to select the random effects in linear mixed models
Michela Battauz and Paolo Vidoni
Comparing two spatial variables with the probability of agreement
Jonathan Acosta, Ronny Vallejos, Aaron M. Ellison, Felipe Osorio, and Mario de Castro
High-dimensional sparse vine copula regression with application to genomic prediction
Ozge Sahin and Claudia Czado
Semi-supervised transfer learning for evaluation of model classification performance
Linshanshan Wang, Xuan Wang, Katherine P. Liao, and Tianxi Cai
From local to global gene co-expression estimation using single-cell RNA-seq data
Jinjin Tian, Jing Lei, and Kathryn Roeder
Simultaneous variable selection and estimation in semiparametric regression of mixed panel count data
Lei Ge, Tao Hu, and Yang Li
Two-phase designs with failure time processes subject to non-susceptibility
Fangya Mao, Li C. Cheung, and Richard J. Cook
Sparse ordinal discriminant analysis
Sangil Han, Minwoo Kim, Sungkyu Jung, and Jeongyoun Ahn
Penalized deep partially linear Cox models with application to CT scans of lung cancer patients
Yuming Sun, Jian Kang, Chinmay Haridas, Nicholas R. Mayne, Alexandra L. Potter, Chi-Fu Jeffrey Yang, David C. Christiani, and Yi Li
Using instrumental variables to address unmeasured confounding in causal mediation analysis
Kara E. Rudolph, Nicholas Williams, and Ivan Diaz
Multiply robust estimators in longitudinal studies with missing data under control-based imputation
Siyi Liu, Shu Yang, Yilong Zhang, and Guanghan (Frank) Liu
A rank-based approach to evaluate a surrogate marker in a small sample setting
Layla Parast, Tianxi Cai, and Lu Tian
A flexible framework for spatial capture-recapture with unknown identities
Paul van Dam-Bates, Michail Papathomas, Ben Stevenson, Rachel Fewster, Daniel Turek, Frances Stewart, and David Borchers
Inferring HIV transmission patterns from viral deep-sequence data via latent typed point processes
Fan Bu, Joseph Kagaayi, Mary Kate Grabowski, Oliver Ratmann, and Jason Q. Xu
Nonparametric predictive model for sparse and irregular longitudinal data
Shixuan Wang, Seonjin Kim, Hyunkeun Cho, and Won Chang
Clustering blood donors via mixtures of product partition models with covariates
Raffaele Argiento, Riccardo Corradin, Alessandra Guglielmi, and Ettore Lanzarone
A generalized Phase 1-2-3 design integrating dose optimization with confirmatory treatment comparison
Yong Zang, Peter F. Thall, and Ying Yuan
Randomized phase II selection design with order constrained strata
Yi Chen and Menggang Yu
Robust data integration from multiple external sources for generalized linear models with binary outcomes
Kyuseong Choi, Jeremy M.G. Taylor, and Peisong Han
Multi-objective tree-based reinforcement learning for estimating tolerant dynamic treatment regimes
Yao Song and Lu Wang
Proportional rates models for multivariate panel count data
Yangjianchen Xu, Donglin Zeng, and D. Y. Lin
Efficient designs and analysis of two-phase studies with longitudinal binary data
Chiara Di Gravio, Jonathan S. Schildcrout, and Ran Tao
A Bayesian survival treed hazards model using latent Gaussian processes
Richard D. Payne, Nilabja Guha, and Bani K. Mallick
Personalized treatment selection via product partition models with covariates
Matteo Pedone, Raffaele Argiento, and Francesco C. Stingo
Homogeneity pursuit and variable selection in regression models for multivariate abundance data
Francis K.C. Hui, Luca Maestrini, and Alan H. Welsh
Principal stratification analysis of noncompliance with time-to-event outcomes
Bo Liu, Lisa Wruck, and Li Fan
Incorporating graph information in Bayesian factor analysis with robust and adaptive shrinkage priors
Qiyiwen Zhang, Changgee Chang, Li Shen, and Qi Long
Efficient estimation for left-truncated competing risks regression for case-cohort studies
Xi Fang, Kwang Woo Ahn, Jianwen Cai, and Soyoung Kim
Adaptive sequential surveillance with network and temporal dependence
Ivana Malenica, Jeremy R. Coyle, Mark J. van der Laan, and Maya L. Petersen
Multiple augmented reduced rank regression for pan-cancer analysis
Jiuzhou Wang and Eric F. Lock
Biometric Practice
Soft classification and regression analysis of audiometric phenotypes of age-related hearing loss
Ce Yang, Benjamin Langworthy, Sharon Curhan, Kenneth I. Vaden Jr., Gary Curhan, Judy R. Dubno, and Molin Wang
Bayesian two-stage modeling of longitudinal and time-to-event data with an integrated Brownian motion covariance structure
Anushka Palipana, Seongho Song, Nishant Gupta, and Rhonda Szczesniak
A scalar-on-quantile-function approach for estimating short-term health effects of environmental exposures
Yuzi Zhang, Howard H. Chang, Joshua L. Warren, and Stefanie T. Ebelt
Inferring a directed acyclic graph of phenotypes from GWAS summary statistics
Rachel Zilinskas, Chunlin Li, Xiaotong Shen, Wei Pan, and Tianzhong Yang
Estimation of the causal effects of time-varying treatments in nested case-control studies using marginal structural Cox models
Yoshinori Takeuchi, Yasuhiro Hagiwara, Sho Komukai, and Yutaka Matsuyama
Merging or ensembling: integrative analysis in multiple neuroimaging studies
Yue Shan, Chao Huang, Yun Lia, and Hongtu Zhu
Estimating the effect of latent time-varying count exposures using multiple lists
Jung Yeon Won, Michael R. Elliott, Emma V. Sanchez-Vaznaugh, and Brisa Sanchez
Individualized treatment rule characterization via a value function surrogate
Nikki L. B. Freeman, Sydney E. Browder, Katharine L. McGinigle, and Michael R. Kosorok
Quantifying the HIV reservoir with dilution assays and deep viral sequencing
Sarah C. Lotspeich, Brian D. Richardson, Pedro L. Baldoni, Kimberly P. Enders, and Michael G. Hudgens
That’s not the Mona Lisa! How to interpret spatial capture-recapture density surface estimates
Ian Durbach, Rishika Chopara, David L. Borchers, Rachel Phillip, Koustubh Sharma, and Ben C. Stevenson
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
Reader Reaction
Adaptive selection of the optimal strategy to improve precision and power in randomized trials
Laura B. Balzer, Erica Cai, Lucas Godoy Garraza, and Pracheta Amaranath
Book Reviews
Bayesian nonparametric for causal inference and missing data by Michael J. Daniels, Antonio Linero, and Jason Roy, CRC Press, 2023 ISBN-13: 978-0367341008, https://www.routledge.com/Bayesian-Nonparametrics-for-Causal-Inference-and-Missing-Data/Daniels-Linero-Roy/p/book/9780367341008
Li-Pang Chen
Sparse graphical modeling for high dimensional data: a paradigm of conditional independence tests by Faming Liang and Bochao Jia, CRC Press, 2023 ISBN-13: 978-0367183738, https://www.routledge.com/Sparse-Graphical-Modeling-for-High-Dimensional-Data-A-Paradigm-of-Conditional/Liang-Jia/p/book/9780367183738
Li-Pang Chen
Papers to appear in future issues of Biometrics
Bayesian meta-analysis of penetrance for cancer risk
Thanthirige Ruberu, Danielle Lakshika Braun, Giovanni Parmigiani, and Swati Biswas
Discussion
Gianluca Baio
Discussion
Peter Müller and Bernardo Flores
Discussion
Sudipto Banerjee
Discussion
Moreno Ursino and Sarah Zohar
Discussion
Paul Gustafson
Rejoinder to the discussion on "Bayesian meta-analysis of penetrance for cancer risk"
Thanthirige Ruberu, Danielle Lakshika Braun, Giovanni Parmigiani, and Swati Biswas
On exact randomization-based covariate-adjusted confidence intervals
Jacob Fiksel
Causal inference for time-to-event data with a cured subpopulation
Yi Wang, Yuhao Deng, and Xiao-Hua Zhou
Flagging unusual clusters based on linear mixed models using weighted and self-calibrated predictors
Charles E. McCulloch, John M. Neuhaus, and Ross D. Boylan
Case weighted power priors for hybrid control analyses with time-to-event data
Evan Kwiatkowski, Jiawen Zhu, Xiao Li, Herbert Pang, Grazyna Lieberman, and Matthew A. Psioda
Estimating the size of a closed population by modeling latent and observed heterogeneity
Francesco Bartolucci and Antonio Forcina
Confounder-dependent Bayesian mixture model: Characterizing heterogeneity of causal effects in air pollution epidemiology
Dafne Zorzetto, Falco Joannes Bargagli Stoffi, Antonio Canale, and Francesca Dominici
High-dimensional multi-subject time series transition matrix inference with application to brain connectivity analysis
Xiang Lyu, Jian Kang, and Lexin Li
LEAP: The latent exchangeability prior for borrowing information from historical data
Ethan M. Alt, Xiuya Chang, Xun Jiang, Qing Liu, May Mo, H. Amy Xia, and Joseph G. Ibrahim
Behavioral carry-over effect and power consideration in crossover trials
Danni Shi and Ting Ye
Deep partially linear Cox model for current status data
Qiang Wu, Xingwei Tong, and Xingqiu Zhao
PathGPS: Discover shared genetic architecture using GWAS summary data
Zijun Gao, Trevor Hastie, and Qingyuan Zhao
Well-spread samples with dynamic sample sizes
Blair Robertson, Chris Price, and Marco Reale
Single proxy control
Chan Park, David B. Richardson, and Eric J. Tchetgen Tchetgen
Topical hidden genome: discovering latent cancer mutational topics using a Bayesian multilevel context-learning approach
Saptarshi Chakraborty, Zoe Guan, Colin B. Begg, and Ronglai Shen
Identifying temporal pathways using biomarkers in the presence of latent non-Gaussian components
Shanghong Xie, Donglin Zeng, and Yuanjia Wang
Reader Reaction: Direct and indirect treatment effects in the presence of semi-competing risks
Yuhao Deng, Yi Wang, and Xiao-Hua Zhou
Addressing age measurement errors in fish growth estimation from length-stratified samples
Nan Zheng, Atefeh Kheirollahi, and Yildiz Yilmaz
High-dimensional covariate-augmented overdispersed Poisson factor model
Wei Liu and Qingzhi Zhong
Testing conditional quantile independence with functional covariate
Yongzhen Feng, Jie Li, and Xiaojun Song
Regression models for average hazard
Hajime Uno, Lu Tian, Miki Horiguchi, Satoshi Hattori, and Kenneth L. Kehl
Efficient data integration under prior probability shift
Ming-Yueh Huang, Jing Qin, and Chiung-Yu Huang
Sequential covariate-adjusted randomization via hierarchically minimizing Mahalanobis distance and marginal imbalance
Haoyu Yang, Yichen Qin, Yang Li, and Feifang Hu
Doubly robust estimation and sensitivity analysis for marginal structural quantile models
Chao Cheng, Liangyuan Hu, and Fan Li
Integrating randomized and observational studies to estimate optimal dynamic treatment regimes
Anna Batorsky, Kevin J. Anstrom, and Donglin Zeng