Papers to Appear

Biometric Methodology

The Cox-Polya-Gamma algorithm for flexible Bayesian inference of multilevel survival models

Benny Ren, Jeffrey S. Morris, and Ian Barnett

Binary regression and classification with covariates in metric spaces

Yinan Lin and Zhenhua Lin

Exploring the heterogeneity in recurrent episode lengths based on quantile regression

Yi Liu, Guillermo E. Umpierrez, and Limin Peng

Statistical significance of clustering for count data

Yifan Dai, Di Wu, and Yufeng Liu

Estimating associations between cumulative exposure and health via generalized distributed lag non-linear models using penalized splines

Tianyi Pan, Hwashin Hyun Shin, Glen McGee, and Alex Stringer

Nonparametric Bayesian approach for dynamic borrowing of historical control data

Tomohiro Ohigashi, Kazushi Maruo, Takashi Sozu, and Masahiko Gosho

Joint disease mapping for bivariate count data with residual correlation due to unknown number of common cases

Edouard Chatignoux, Zoé Uhry, Laurent Remontet, and Isabelle Albert

A monotone single-index model for spatially-referenced multistate current status data

Snigdha Das, Minwoo Chae, Debdeep Pati, and Dipankar Bandyopadhyay

Model robust designs for dose-response models

Belmiro P.M. Duarte, Anthony C. Atkinson and Nuno M.C. Oliveira

Smooth and shape-constrained quantile distributed lag models

Yisen Jin, Aaron J. Molstad, Ander Wilson, and Joseph Antonelli

Semi-supervised linear regression: enhancing efficiency and robustness in high dimensions

Kai Chen and Yuqian Zhang

Mastering rare event analysis: Subsample-size determination in Cox and logistic regressions

Tal Agassi, Nir Keret, and Malka Gorfine

High-dimensional multi-study multi-modality covariate-augmented generalized factor model

Wei Liu and Qingzhi Zhong

Regression analysis of interval-censored failure time data with change points and a cured subgroup

Yichen Lou, Mingyue Du, and Xinyuan Song

Cumulative incidence function estimation using population-based biobank data

M. Gorfine, D. M. Zucker, and Shoval Shoham

Causal machine learning for heterogeneous treatment effects in the presence of missing outcome data

Matthew Pryce, Karla Diaz-Ordaz, Ruth H. Keogh, and Stijn Vansteelandt

Covariance-on-covariance regression

Yi Zhao and Yize Zhao

Valid and efficient inference for nonparametric variable importance in two-phase studies

Guorong Dai, Raymond J. Carroll, and Jinbo Chen

Improved prediction and flagging of extreme random effects for non-Gaussian outcomes using weighted methods

John Neuhaus, Charles McCulloch, and Ross Boylan

Multiple tests for restricted mean time lost with competing risks data

Merle Munko, Dennis Dobler and Marc Ditzhaus

Frequency band analysis of nonstationary multivariate time series

Raanju R. Sundararajan and Scott A. Bruce

Two-stage estimators for spatial confounding with point-referenced data

Nate Wiecha, Jane A. Hoppin, and Brian J. Reich

A positivity robust strategy to study effects of switching treatment

Matias Janvin, Pål Christie Ryalen, Aaron L. Sarvet, and Mats J. Stensrud

Adjusted predictions for generalized estimating equations

Francis K.C. Hui, Samuel Muller, and A. H. Welsh

Tree-based additive noise directed acyclic graphical models for nonlinear causal discovery with interactions

Fangting Zhou, Kejun He, and Yang Ni

Precision generalized Phase I-II designs

Saijun Zhao, Peter F. Thall, Ying Yuan, Juhee Lee, Pavlos Msaouel, and Yong Zang

Doubly robust nonparametric estimators of the predictive value of covariates for survival data

Torben Martinussen and Mark J. van der Laan

Biometric Practice

Spatially aware adjusted Rand index for evaluating spatial transcriptomics clustering

Yinqiao Yan, Xiangnan Feng, and Xiangyu Luo

A Bayesian semiparametric mixture model for clustering zero-inflated microbiome data

Suppapat Korsurat and Matthew D. Koslovsky

A group distributional ICA method for decomposing multi-subject diffusion tensor imaging

Guangming Yang, Ben Wu, Jian Kang, and Ying Guo

Bayesian inference for copy number intra-tumoral heterogeneity from single-cell RNA-sequencing data

PuXue Qiao, Chun Fung Kwok, Guoqi Qian, and Davis J. McCarthy

Revisiting optimal allocations for binary responses: Insights from considering type-I error rate control

Lukas Pin, Sofia S. Villar, and William F. Rosenberger

Sensitivity analysis for attributable effects in case$^2$ studies

Kan Chen, Ting Ye, and Dylan Small

Evaluating longitudinal treatment effects for Duchenne muscular dystrophy using dynamically enriched Bayesian small sample, sequential, multiple assignment randomized trial (snSMART)

Sidi Wang, Satrajit Roychoudhury, and Kelley M. Kidwell

Semiparametric joint modeling to estimate the treatment effect on a longitudinal surrogate with application to chronic kidney disease trials

Xuan Wang, Jie Zhou, Layla Parast, and Tom Greene

Negative binomial mixed effects location-scale models for intensive longitudinal count-type physical activity data provided by wearable devices

Qianheng Ma, Genevieve F. Dunton, and Donald Hedeker

Simple simulation based reconstruction of incidence rates from death data

Simon N. Wood

Using model-assisted calibration methods to improve efficiency of regression analyses using two-phase samples or pooled samples under complex survey designs

Lingxiao Wang

Inference on age-specific fertility in ecology and evolution. Learning from other disciplines and improving the state of the art

Fernando Colchero

A flexible framework for N-mixture occupancy models: applications to breeding bird surveys

Huu-Dinh Huynh, J. Andrew Royle, and Wen-Han Hwang

Sparse two-stage Bayesian meta-analysis for individualized treatments

Junwei Shen, Erica E. M. Moodie, and Shirin Golchi

Book Reviews

Introduction to environmental data science by Jerry D. Davis, Chapman and Hall/CRC, 2023, ISBN: 9781003317821 https://www.routledge.com/Introduction-to-environmental-data-science/Davis/p/book/9781003317821

Lianne Sheppard and Magali N. Blanco

Mixture models: parametric, semiparametric, and new directions by Weixin Yao and Sijia Xiang, Chapman and Hall/CRC, 2024, ISBN: 9780367481827 https://www.routledge.com/Mixture-models-parametric-semiparametric-and-new-directions/Yao-Xiang/p/book/9780367481827

Li-Pang Chen

Development of gene therapies: strategic, scientific, regulatory, and access considerations by Avery McIntosh and Oleksandr Sverdlov, Chapman and Hall/CRC, 2024, ISBN: 9781032136554 https://www.routledge.com/Development-of-Gene-Therapies-Strategic-Scientific-Regulatory-and-Access-Considerations/McIntosh-Sverdlov/p/book/9781032136554

Ying Yuan

Change point analysis for time series by Lajos Horváth and Gregory Rice, Springer, 2024, ISBN: 9783031516085https://link.springer.com/book/10.1007/978-3-031-51609-2 

Fang Han

Corrections

Correction to: Evaluating the effects of high-throughput structural neuroimaging predictors on whole-brain functional connectome outcomes via network-based matrix-on-vector regression 

Correction to: Propensity weighting plus adjustment in proportional hazards model is not doubly robust

Papers to appear in future issues of Biometrics

Letter to the Editors: Comments on ‘Statistical inference on change points in generalized semiparametric segmented models’ by Yang et al. (2025)

Vito M.R. Muggeo

Rejoinder to Letter to the Editors “Comments on ‘Statistical inference on change points in generalized semiparametric segmented models’ by Yang et al. (2025)” by Vito M.R. Muggeo

Guangyu Yang and Min Zhang

Randomized optimal selection design for dose optimization

Shuqi Wang, Ying Yuan, and Suyu Liu

Causal inference with misspecified network interference structure

Bar Weinstein and Daniel Nevo

Discussion on “Causal Inference with Misspecified Network Interference Structure” by Bar Weinstein and Daniel Nevo

Fei Fang and Laura Forastiere

Discussion on “Causal Inference with Misspecified Network Interference Structure” by Bar Weinstein and Daniel Nevo

Chan Park and Hyunseung Kang

Discussion on “Causal Inference with Misspecified Network Interference Structure” by Bar Weinstein and Daniel Nevo

Fredrik Sävje

Discussion on “Causal Inference with Misspecified Network Interference Structure” by Bar Weinstein and Daniel Nevo

Daniel Malinsky

Inverse-intensity weighted GEEs for longitudinal data subject to irregular observation: which variables should be included in the visit rate model?

Eleanor M. Pullenayegum and Di Shan

Deep partially linear transformation model for right-censored survival data

Junkai Yin, Yue Zhang, and Zhangsheng Yu

SPLasso for high-dimensional additive hazards regression with covariate measurement error

Jiarui Zhang, Hongsheng Liu, Xin Chen, and Jinfeng Xu

Distal causal excursion effects: Modeling long-term effects of time-varying treatments in micro-randomized trials

Tianchen Qian

Statistical inference for heterogeneous treatment effect with right-censored data from synthesizing randomized clinical trials and real-world data

Guangcai Mao, Shu Yang, and Xiaofei Wang

Robust integration of external control data in randomized trials

Rickard Karlsson, Guanbo Wang, Piersilvio De Bartolomeis, Jesse H. Krijthe, and Issa J. Dahabreh

A meta-learning method for estimation of causal excursion effects to assess time-varying moderation

Jieru Shi and Walter Dempsey

Double robust conditional independence test for novel biomarkers given established risk factors with survival data

Baoying Yang, Jing Qin, Jing Ning, and Yukun Liu

A regularized continuous-time hidden Markov model for identifying latent state transition patterns of poly-tobacco use

Xinyu Yan, Ji-Hyun Lee, and Xiangyang Lou

Bayesian scalar-on-image regression with spatial interactions for modeling Alzheimer’s disease

Nilanjana Chakraborty, Qi Long, and Suprateek Kundu

Bridging the gap between design and analysis: Randomization inference and sensitivity analysis for matched observational studies with treatment doses

Jeffrey Zhang and Siyu Heng

Variable importance measures for heterogeneous treatment effects

Oliver J. Hines, Karla Diaz-Ordaz, and Stijn Vansteelandt

A Bayesian collocation integral method for system identification of ordinary differential equations

Mingwei Xu, Samuel W.K. Wong, and Peijun Sang

Clarifying the role of the Mantel-Haenszel risk difference estimator in randomized clinical trials

Xiaoyu Qui, Yuhan Qian, Jaehwan Yi, Jinqiu Wang, Yu Du, Yanyao Yi, and Ting Ye

Adaptive stratified sampling design in two-phase studies for average causal effect estimation

Min Zeng, Qiyu Wang, Zijian Sui, Hong Zhang, and Jinfeng Xu

Federated double machine learning for high-dimensional semiparametric models

Kai Kang, Zhihao Wu, Xinjie Qian, Xinyuan Song, and Hongtu Zhu

Bayesian monotone single-index quantile regression model with bounded response and misaligned functional covariates

Shengxian Ding, Debajyoti Sinha, Greg Hajcak, Roman Kotov, and Chao Huang

Generalized nonparametric temporal modeling of recurrent events with application to a malaria vaccine trial

Fei Heng, Yanqing Sun, Jing Xu, and Peter B. Gilbert

Flexible and efficient estimation of causal effects with error-prone exposures: A control variates approach for measurement error

Keith Barnatchez, Rachel Nethery, Bryan E. Shepherd, Giovanni Parmigiani, and Kevin P. Josey

Estimating heterogeneous treatment effects for general responses

Zijun Gao and Trevor Hastie

Joint Bayesian additive regression trees for multiple non-linear dependency networks

Licai Huang, Christine B. Peterson, and Min Jin Ha

A semiparametric Gaussian mixture model with spatial dependence and its application to whole-slide image clustering analysis

Baichen Yu, Jin Liu, and Hansheng Wang

Analysis of cross-platform health communication with a network approach

Xinyan Fan, Mengque Liu, and Shuangge Ma

Large row-constrained supersaturated designs for high-throughput screening

Byran J. Smucker, Stephen E. Wright, Isaac Williams, Richard C. Page, Andor J. Kiss, Surendra Bikram Silwal, Maria Weese, and David J. Edwards

Flexible Bayesian quantile regression for counts via generative modeling

Yuta Yamauchi, Genya Kobayashi, and Shonosuke Sugasawa

Super learner for survival prediction in case-cohort and generalized case-cohort studies

Haolin Li, Haibo Zhou, David Couper, and Jianwen Cai

Entrywise splitting cross-validation in generalized factor models: From sample splitting to entrywise splitting

Zhijing Wang

Stable survival extrapolation using mortality projections

Anastasios Apsemidis and Nikolaos Demiris

A semiparametric method for addressing under-diagnosis using electronic health record data

Weidong Ma, Jordana B. Cohen, and Jinbo Chen

Censoring-robust estimation in fixed sample time-to-event clinical trials with adaptive randomization

Navneet R. Hakhu and Daniel L. Gillen

Prediction of transition probabilities in multi-state models with nested case-control data

Yen Chang, Anastasia Ivanova, Demetrius Albanes, Jason P. Fine, and Yei Eun Shin

Structuring, sequencing, staging, selecting: the 4S method for the longitudinal analysis of multidimensional questionnaires in chronic diseases

Tiphaine Saulnier, Wassilios G. Meissner, Margherita Fabbri, Alexandra Foubert-Samier, and Cécile Proust-Lima

Statistical inference on high dimensional covariate-dependent Gaussian graphical regressions

Xuran Meng, Jingfei Zhang, and Yi Li

Comment on “Double robust conditional independence test for novel biomarkers given established risk factors with survival data”

Lucas Kook