Biometrics

1999 - 2023

From The International Biometric Society
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Volume 79, issue 4, 2023

Optimal test procedures for multiple hypotheses controlling the familywise expected loss pp. 2781-2793

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 pp. 2794-2797

Yoav Benjamini, Ruth Heller, Abba Krieger and Saharon Rosset

Discussion of “Optimal test procedures for multiple hypotheses controlling the familywise expected loss” by Willi Maurer, Frank Bretz, and Xiaolei Xun pp. 2798-2801

Sudipto Banerjee

Discussion of “Optimal test procedures for multiple hypotheses controlling the familywise expected loss” by Willi Maurer, Frank Bretz, and Xiaolei Xun pp. 2802-2805

L.M. LaVange, E.M. Alt and J.G. Ibrahim

Discussion on “Optimal test procedures for multiple hypotheses controlling the familywise expected loss” by Willi Maurer, Frank Bretz, and Xiaolei Xun pp. 2806-2810

Werner Brannath

Rejoinder to discussions on “Optimal test procedures for multiple hypotheses controlling the familywise expected loss” pp. 2811-2814

Willi Maurer, Frank Bretz and Xiaolei Xun

Optimizing treatment allocation in randomized clinical trials by leveraging baseline covariates pp. 2815-2829

Wei Zhang, Zhiwei Zhang and Aiyi Liu

Estimating optimal individualized treatment rules with multistate processes pp. 2830-2842

Giorgos Bakoyannis

Stabilized direct learning for efficient estimation of individualized treatment rules pp. 2843-2856

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

SAM: Self‐adapting mixture prior to dynamically borrow information from historical data in clinical trials pp. 2857-2868

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

Regression‐based multiple treatment effect estimation under covariate‐adaptive randomization pp. 2869-2880

Yujia Gu, Hanzhong Liu and Wei Ma

Interim monitoring of sequential multiple assignment randomized trials using partial information pp. 2881-2894

Cole Manschot, Eric Laber and Marie Davidian

Covariate‐adjusted response‐adaptive designs based on semiparametric approaches pp. 2895-2906

Hai Zhu and Hongjian Zhu

DROID: dose‐ranging approach to optimizing dose in oncology drug development pp. 2907-2919

Beibei Guo and Ying Yuan

Relative contrast estimation and inference for treatment recommendation pp. 2920-2932

Muxuan Liang and Menggang Yu

Hierarchical nuclear norm penalization for multi‐view data integration pp. 2933-2946

Sangyoon Yi, Raymond Ka Wai Wong and Irina Gaynanova

An efficient data integration scheme for synthesizing information from multiple secondary datasets for the parameter inference of the main analysis pp. 2947-2960

Chixiang Chen, Ming Wang and Shuo Chen

Combining observational and experimental datasets using shrinkage estimators pp. 2961-2973

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

Optimal sampling for positive only electronic health record data pp. 2974-2986

Seong‐H. Lee, Yanyuan Ma, Ying Wei and Jinbo Chen

Explaining transmission rate variations and forecasting epidemic spread in multiple regions with a semiparametric mixed effects SIR model pp. 2987-2997

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

Identifying and estimating effects of sustained interventions under parallel trends assumptions pp. 2998-3009

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

Additive subdistribution hazards regression for competing risks data in case‐cohort studies pp. 3010-3022

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

Nonparametric failure time: Time‐to‐event machine learning with heteroskedastic Bayesian additive regression trees and low information omnibus Dirichlet process mixtures pp. 3023-3037

Rodney A. Sparapani, Brent R. Logan, Martin J. Maiers, Purushottam W. Laud and Robert E. McCulloch

Estimation of time‐specific intervention effects on continuously distributed time‐to‐event outcomes by targeted maximum likelihood estimation pp. 3038-3049

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

Information criteria for detecting change‐points in the Cox proportional hazards model pp. 3050-3065

Ryoto Ozaki and Yoshiyuki Ninomiya

An accelerated failure time regression model for illness–death data: A frailty approach pp. 3066-3081

Lea Kats and Malka Gorfine

Group variable selection for the Cox model with interval‐censored failure time data pp. 3082-3095

Yuxiang Wu, Hui Zhao and Jianguo Sun

Ensuring valid inference for Cox hazard ratios after variable selection pp. 3096-3110

Kelly Van Lancker, Oliver Dukes and Stijn Vansteelandt

A semiparametric Cox–Aalen transformation model with censored data pp. 3111-3125

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

Efficient and flexible estimation of natural direct and indirect effects under intermediate confounding and monotonicity constraints pp. 3126-3139

Kara E. Rudolph, Nicholas Williams and Iván Díaz

Improved inference for doubly robust estimators of heterogeneous treatment effects pp. 3140-3152

Heejun Shin and Joseph Antonelli

Prior and posterior checking of implicit causal assumptions pp. 3153-3164

Antonio R. Linero

Transportability of causal inference under random dynamic treatment regimes for kidney–pancreas transplantation pp. 3165-3178

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

Entropy balancing for causal generalization with target sample summary information pp. 3179-3190

Rui Chen, Guanhua Chen and Menggang Yu

Individualized causal discovery with latent trajectory embedded Bayesian networks pp. 3191-3202

Fangting Zhou, Kejun He and Yang Ni

A self‐censoring model for multivariate nonignorable nonmonotone missing data pp. 3203-3214

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

Instability of inverse probability weighting methods and a remedy for nonignorable missing data pp. 3215-3226

Pengfei Li, Jing Qin and Yukun Liu

A double‐robust test for high‐dimensional gene coexpression networks conditioning on clinical information pp. 3227-3238

Maomao Ding, Ruosha Li, Jin Qin and Jing Ning

A Bayesian zero‐inflated Dirichlet‐multinomial regression model for multivariate compositional count data pp. 3239-3251

Matthew D. Koslovsky

Bayesian nonparametric adjustment of confounding pp. 3252-3265

Chanmin Kim, Mauricio Tec and Corwin Zigler

Bayesian model selection for generalized linear mixed models pp. 3266-3278

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

Functional Bayesian networks for discovering causality from multivariate functional data pp. 3279-3293

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

Bayesian functional data analysis over dependent regions and its application for identification of differentially methylated regions pp. 3294-3306

Suvo Chatterjee, Shrabanti Chowdhury, Duchwan Ryu and Sanjib Basu

Latent factor model for multivariate functional data pp. 3307-3318

Ruonan Li and Luo Xiao

Nonlinear function‐on‐scalar regression via functional universal approximation pp. 3319-3331

Ruiyan Luo and Xin Qi

Homogeneity tests of covariance for high‐dimensional functional data with applications to event segmentation pp. 3332-3344

Ping‐Shou Zhong

Latent deformation models for multivariate functional data and time‐warping separability pp. 3345-3358

Cody Carroll and Hans‐Georg Müller

Bi‐level structured functional analysis for genome‐wide association studies pp. 3359-3373

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

Asynchronous and error‐prone longitudinal data analysis via functional calibration pp. 3374-3387

Xinyue Chang, Yehua Li and Yi Li

Simultaneous selection and inference for varying coefficients with zero regions: a soft‐thresholding approach pp. 3388-3401

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

Combining mixed effects hidden Markov models with latent alternating recurrent event processes to model diurnal active–rest cycles pp. 3402-3417

Benny Ren and Ian Barnett

Longitudinal incremental propensity score interventions for limited resource settings pp. 3418-3430

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

Flexible joint modeling of mean and dispersion for the directional tuning of neuronal spike counts pp. 3431-3444

María Alonso‐Pena, Irène Gijbels and Rosa M. Crujeiras

Sparse estimation in semiparametric finite mixture of varying coefficient regression models pp. 3445-3457

Abbas Khalili, Farhad Shokoohi, Masoud Asgharian and Shili Lin

Conditional inference in cis‐Mendelian randomization using weak genetic factors pp. 3458-3471

Ashish Patel, Dipender Gill, Paul Newcombe and Stephen Burgess

Competition‐based control of the false discovery proportion pp. 3472-3484

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

Multiresolution categorical regression for interpretable cell‐type annotation pp. 3485-3496

Aaron J. Molstad and Keshav Motwani

False discovery rate‐controlled multiple testing for union null hypotheses: a knockoff‐based approach pp. 3497-3509

Ran Dai and Cheng Zheng

Analyzing data in complicated 3D domains: Smoothing, semiparametric regression, and functional principal component analysis pp. 3510-3521

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

Detecting the spatial clustering of exposure–response relationships with estimation error: a novel spatial scan statistic pp. 3522-3532

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

A seasonality‐adjusted sequential test for vaccine safety surveillance pp. 3533-3548

Rex Shen, Keran Moll, Ying Lu and Lu Tian

On interquantile smoothness of censored quantile regression with induced smoothing pp. 3549-3563

Zexi Cai and Tony Sit

A stochastic block Ising model for multi‐layer networks with inter‐layer dependence pp. 3564-3573

Jingnan Zhang, Chengye Li and Junhui Wang

Generating designs for comparative experiments with two blocking factors pp. 3574-3585

Nha Vo‐Thanh and Hans‐Peter Piepho

Bayesian design of multi‐regional clinical trials with time‐to‐event endpoints pp. 3586-3598

Nathan William Bean, Joseph George Ibrahim and Matthew Austin Psioda

Sparse Bayesian modeling of hierarchical independent component analysis: Reliable estimation of individual differences in brain networks pp. 3599-3611

Joshua Lukemire, Giuseppe Pagnoni and Ying Guo

Dynamic enrichment of Bayesian small‐sample, sequential, multiple assignment randomized trial design using natural history data: a case study from Duchenne muscular dystrophy pp. 3612-3623

Sidi Wang, Kelley M. Kidwell and Satrajit Roychoudhury

Bayesian causal inference for observational studies with missingness in covariates and outcomes pp. 3624-3636

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

Spatially adaptive calibrations of airbox PM2.5 data pp. 3637-3649

ShengLi Tzeng, Chi‐Wei Lai and Hsin‐Cheng Huang

Spatial modeling of Mycobacterium tuberculosis transmission with dyadic genetic relatedness data pp. 3650-3663

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

Latent trajectory models for spatio‐temporal dynamics in Alaskan ecosystems pp. 3664-3675

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

Imputation‐based Q‐learning for optimizing dynamic treatment regimes with right‐censored survival outcome pp. 3676-3689

Lingyun Lyu, Yu Cheng and Abdus S. Wahed

Analysis of dynamic restricted mean survival time based on pseudo‐observations pp. 3690-3700

Zijing Yang, Chengfeng Zhang, Yawen Hou and Zheng Chen

Study design for restricted mean time analysis of recurrent events and death pp. 3701-3714

Lu Mao

Finding influential subjects in a network using a causal framework pp. 3715-3727

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

Causal mediation analysis using high‐dimensional image mediator bounded in irregular domain with an application to breast cancer pp. 3728-3738

Shu Jiang and Graham A. Colditz

Correcting for bias due to mismeasured exposure history in longitudinal studies with continuous outcomes pp. 3739-3751

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

Nonlinear multilevel joint model for individual lesion kinetics and survival to characterize intra‐individual heterogeneity in patients with advanced cancer pp. 3752-3763

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

Analyzing clustered continuous response variables with ordinal regression models pp. 3764-3777

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

A nonparametric test of group distributional differences for hierarchically clustered functional data pp. 3778-3791

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

Bayesian inference for a principal stratum estimand on recurrent events truncated by death pp. 3792-3802

Tianmeng Lyu, Björn Bornkamp, Guenther Mueller‐Velten and Heinz Schmidli

Estimating population size: The importance of model and estimator choice pp. 3803-3817

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

Modeling COVID‐19 contact‐tracing using the ratio regression capture–recapture approach pp. 3818-3830

Dankmar Böhning, Rattana Lerdsuwansri and Patarawan Sangnawakij

A synthetic data integration framework to leverage external summary‐level information from heterogeneous populations pp. 3831-3845

Tian Gu, Jeremy Michael George Taylor and Bhramar Mukherjee

Supervised convex clustering pp. 3846-3858

Minjie Wang, Tianyi Yao and Genevera I. Allen

Conditional cross‐design synthesis estimators for generalizability in Medicaid pp. 3859-3872

Irina Degtiar, Tim Layton, Jacob Wallace and Sherri Rose

A case study of glucose levels during sleep using multilevel fast function on scalar regression inference pp. 3873-3882

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 pp. 3883-3894

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

Constructing time‐invariant dynamic surveillance rules for optimal monitoring schedules pp. 3895-3906

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

Dirichlet process mixture models for the analysis of repeated attempt designs pp. 3907-3915

Michael J. Daniels, Minji Lee and Wei Feng

Sample size and power determination for multiparameter evaluation in nonlinear regression models with potential stratification pp. 3916-3928

Michael J. Martens, Soyoung Kim and Kwang Woo Ahn

Analysis of length‐biased and partly interval‐censored survival data with mismeasured covariates pp. 3929-3940

Li‐Pang Chen and Bangxu Qiu

Melding wildlife surveys to improve conservation inference pp. 3941-3953

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

A proportional incidence rate model for aggregated data to study the vaccine effectiveness against COVID‐19 hospital and ICU admissions pp. 3954-3967

Ping Yan, Muhammad Abu Shadeque Mullah and Ashleigh Tuite

A second evidence factor for a second control group pp. 3968-3980

Paul R. Rosenbaum

Efficient algorithms for building representative matched pairs with enhanced generalizability pp. 3981-3997

Bo Zhang

How to analyze continuous and discrete repeated measures in small‐sample cross‐over trials? pp. 3998-4011

Johan Verbeeck, Martin Geroldinger, Konstantin Thiel, Andrew Craig Hooker, Sebastian Ueckert, Mats Karlsson, Arne Cornelius Bathke, Johann Wolfgang Bauer, Geert Molenberghs and Georg Zimmermann

Statistical inference and machine learning for big data by Mayer Alvo, Springer Cham. 2022. pp. 431. EUR 129.99. ISBN‐13: 978‐3‐031‐06783‐9 pp. 4013-4013

Li‐Pang Chen

Bioinformatics methods: From omics to next generation sequencing By Shili Lin, Denise Scholtens, Sujay Datta, Boca Raton, FL: Chapman & Hall. 2023. pp. 350. ISBN 9781498765152 pp. 4014-4016

Yu‐Chiao Chiu

Volume 79, issue 3, 2023

Structural cumulative survival models for estimation of treatment effects accounting for treatment switching in randomized experiments pp. 1597-1609

Andrew Ying and Eric J. Tchetgen Tchetgen

Dimension reduction for integrative survival analysis pp. 1610-1623

Aaron J. Molstad and Rohit K. Patra

Concordance indices with left‐truncated and right‐censored data pp. 1624-1634

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

Joint inference for competing risks data using multiple endpoints pp. 1635-1645

Jiyang Wen, Chen Hu and Mei‐Cheng Wang

Maximum likelihood estimation in the additive hazards model pp. 1646-1656

Chengyuan Lu, Jelle Goeman and Hein Putter

Penalized estimation of frailty‐based illness–death models for semi‐competing risks pp. 1657-1669

Harrison T. Reeder, Junwei Lu and Sebastien Haneuse

Marginal proportional hazards models for clustered interval‐censored data with time‐dependent covariates pp. 1670-1685

Kaitlyn Cook, Wenbin Lu and Rui Wang

Improved semiparametric estimation of the proportional rate model with recurrent event data pp. 1686-1700

Ming‐Yueh Huang and Chiung‐Yu Huang

Non‐parametric estimation of the age‐at‐onset distribution from a cross‐sectional sample pp. 1701-1712

S. Mandal, J. Qin and R.M. Pfeiffer

An information ratio‐based goodness‐of‐fit test for copula models on censored data pp. 1713-1725

Tao Sun, Yu Cheng and Ying Ding

Model uncertainty quantification in Cox regression pp. 1726-1736

Gonzalo García‐Donato, Stefano Cabras and María Eugenia Castellanos

General independent censoring in event‐driven trials with staggered entry pp. 1737-1748

Jasmin Rühl, Jan Beyersmann and Sarah Friedrich

Nonparametric inference of general while‐alive estimands for recurrent events pp. 1749-1760

Lu Mao

Two‐level Bayesian interaction analysis for survival data incorporating pathway information pp. 1761-1774

Xing Qin, Shuangge Ma and Mengyun Wu

A Bayesian multivariate mixture model for high throughput spatial transcriptomics pp. 1775-1787

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 pp. 1788-1800

Zhongwei Zhang, Reinaldo B. Arellano‐Valle, Marc G. Genton and Raphaël Huser

Integrative Bayesian models using Post‐selective inference: A case study in radiogenomics pp. 1801-1813

Snigdha Panigrahi, Shariq Mohammed, Arvind Rao and Veerabhadran Baladandayuthapani

Bayesian regression analysis of skewed tensor responses pp. 1814-1825

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

Adaptive Bayesian sum of trees model for covariate‐dependent spectral analysis pp. 1826-1839

Yakun Wang, Zeda Li and Scott A. Bruce

Solutions for surrogacy validation with longitudinal outcomes for a gene therapy pp. 1840-1852

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

Subset selection for linear mixed models pp. 1853-1867

Daniel R. Kowal

Grouped generalized estimating equations for longitudinal data analysis pp. 1868-1879

Tsubasa Ito and Shonosuke Sugasawa

Asynchronous functional linear regression models for longitudinal data in reproducing kernel Hilbert space pp. 1880-1895

Ting Li, Huichen Zhu, Tengfei Li and Hongtu Zhu

Contrasting principal stratum and hypothetical strategy estimands in multi‐period crossover trials with incomplete data pp. 1896-1907

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

Optimal multiple testing and design in clinical trials pp. 1908-1919

Ruth Heller, Abba Krieger and Saharon Rosset

Change‐plane analysis for subgroup detection with a continuous treatment pp. 1920-1933

Peng Jin, Wenbin Lu, Yu Chen and Mengling Liu

Efficient targeted learning of heterogeneous treatment effects for multiple subgroups pp. 1934-1946

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

Tensor response quantile regression with neuroimaging data pp. 1947-1958

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

Joint semiparametric models for case‐cohort designs pp. 1959-1971

Weibin Zhong and Guoqing Diao

Multidimensional adaptive P‐splines with application to neurons' activity studies pp. 1972-1985

María Xosé Rodríguez‐Álvarez, María Durbán, Paul H.C. Eilers, Dae‐Jin Lee and Francisco Gonzalez

Combining parametric and nonparametric models to estimate treatment effects in observational studies pp. 1986-1995

Daniel Daly‐Grafstein and Paul Gustafson

Semiparametric estimation of the transformation model by leveraging external aggregate data in the presence of population heterogeneity pp. 1996-2009

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 pp. 2010-2022

Chun Yin Lee, Kin Yau Wong, Kwok Fai Lam and Dipankar Bandyopadhyay

A robust approach for electronic health record–based case‐control studies with contaminated case pools pp. 2023-2035

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

Quantile regression for nonignorable missing data with its application of analyzing electronic medical records pp. 2036-2049

Aiai Yu, Yujie Zhong, Xingdong Feng and Ying Wei

Frequentist model averaging for undirected Gaussian graphical models pp. 2050-2062

Huihang Liu and Xinyu Zhang

Nonparametric scanning tests of homogeneity for hierarchical models with continuous covariates pp. 2063-2075

David Todem, Wei‐Wen Hsu and KyungMann Kim

Identifying alert concentrations using a model‐based bootstrap approach pp. 2076-2088

Kathrin Möllenhoff, Kirsten Schorning and Franziska Kappenberg

Adjusting for publication bias in meta‐analysis via inverse probability weighting using clinical trial registries pp. 2089-2102

Ao Huang, Kosuke Morikawa, Tim Friede and Satoshi Hattori

Elastic analysis of irregularly or sparsely sampled curves pp. 2103-2115

Lisa Steyer, Almond Stöcker and Sonja Greven

A general framework for subgroup detection via one‐step value difference estimation pp. 2116-2126

Dana Johnson, Wenbin Lu and Marie Davidian

Pair‐switching rerandomization pp. 2127-2142

Ke Zhu and Hanzhong Liu

Double reduction estimation and equilibrium tests in natural autopolyploid populations pp. 2143-2156

David Gerard

Center‐augmented ℓ2‐type regularization for subgroup learning pp. 2157-2170

Ye He, Ling Zhou, Yingcun Xia and Huazhen Lin

A general modeling framework for open wildlife populations based on the Polya tree prior pp. 2171-2183

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 pp. 2184-2195

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

Testing weak nulls in matched observational studies pp. 2196-2207

Colin B. Fogarty

Mendelian randomization mixed‐scale treatment effect robust identification and estimation for causal inference pp. 2208-2219

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

Generalized propensity score approach to causal inference with spatial interference pp. 2220-2231

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

Functional data analysis with covariate‐dependent mean and covariance structures pp. 2232-2245

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 pp. 2246-2259

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 pp. 2260-2271

Nina Zhou, Lu Wang and Daniel Almirall

Segmented correspondence curve regression for quantifying covariate effects on the reproducibility of high‐throughput experiments pp. 2272-2285

Feipeng Zhang and Qunhua Li

Concave likelihood‐based regression with finite‐support response variables pp. 2286-2297

K.O. Ekvall and M. Bottai

Boosting distributional copula regression pp. 2298-2310

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

On generalized latent factor modeling and inference for high‐dimensional binomial data pp. 2311-2320

Ting Fung Ma, Fangfang Wang and Jun Zhu

Microbiome subcommunity learning with logistic‐tree normal latent Dirichlet allocation pp. 2321-2332

Patrick LeBlanc and Li Ma

Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors pp. 2333-2345

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 pp. 2346-2356

Ruoqi Yu

CEDAR: communication efficient distributed analysis for regressions pp. 2357-2369

Changgee Chang, Zhiqi Bu and Qi Long

Statistical inference and power analysis for direct and spillover effects in two‐stage randomized experiments pp. 2370-2381

Zhichao Jiang, Kosuke Imai and Anup Malani

Estimating the area under the ROC curve when transporting a prediction model to a target population pp. 2382-2393

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

Inference for the dimension of a regression relationship using pseudo‐covariates pp. 2394-2403

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

Consistent estimation of the number of communities via regularized network embedding pp. 2404-2416

Mingyang Ren, Sanguo Zhang and Junhui Wang

Automated analysis of low‐field brain MRI in cerebral malaria pp. 2417-2429

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 pp. 2430-2443

Jade Xiaoqing 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 pp. 2444-2457

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

Bayesian treatment screening and selection using subgroup‐specific utilities of response and toxicity pp. 2458-2473

Juhee Lee, Peter F. Thall and Pavlos Msaouel

Bayesian hierarchical quantile regression with application to characterizing the immune architecture of lung cancer pp. 2474-2488

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 pp. 2489-2502

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

Fast Bayesian inference for large occupancy datasets pp. 2503-2515

Alex Diana, Emily Beth Dennis, Eleni Matechou and Byron John Treharne Morgan

Comparing COVID‐19 incidences longitudinally per economic sector against the background of preventive measures and vaccination pp. 2516-2524

Florian Stijven, Johan Verbeeck and Geert Molenberghs

Age‐related model for estimating the symptomatic and asymptomatic transmissibility of COVID‐19 patients pp. 2525-2536

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

Correcting delayed reporting of COVID‐19 using the generalized‐Dirichlet‐multinomial method pp. 2537-2550

Oliver Stoner, Alba Halliday and Theo Economou

Assessing exposure‐time treatment effect heterogeneity in stepped‐wedge cluster randomized trials pp. 2551-2564

Lara Maleyeff, Fan Li, Sebastien Haneuse and Rui Wang

Design considerations for two‐stage enrichment clinical trials pp. 2565-2576

Rosamarie Frieri, William Fisher Rosenberger, Nancy Flournoy and Zhantao Lin

Efficient and robust approaches for analysis of sequential multiple assignment randomized trials: Illustration using the ADAPT‐R trial pp. 2577-2591

Lina M. Montoya, Michael R. Kosorok, Elvin H. Geng, Joshua Schwab, Thomas A. Odeny and Maya L. Petersen

Infinite hidden Markov models for multiple multivariate time series with missing data pp. 2592-2604

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 pp. 2605-2618

Fangya Mao and Richard J. Cook

Semiparametric distributed lag quantile regression for modeling time‐dependent exposure mixtures pp. 2619-2632

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

Misdiagnosis‐related harm quantification through mixture models and harm measures pp. 2633-2648

Yuxin Zhu, Zheyu Wang and David Newman‐Toker

Multiwave validation sampling for error‐prone electronic health records pp. 2649-2663

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 pp. 2664-2676

Laura Y. Zhou, Fei Zou and Wei Sun

Neural network on interval‐censored data with application to the prediction of Alzheimer's disease pp. 2677-2690

Tao Sun and Ying Ding

Delivering spatially comparable inference on the risks of multiple severities of respiratory disease from spatially misaligned disease count data pp. 2691-2704

Duncan Lee and Craig Anderson

Associating somatic mutation with clinical outcomes through kernel regression and optimal transport pp. 2705-2718

Paul Little, Li Hsu and Wei Sun

Pattern‐based clustering of daily weigh‐in trajectories using dynamic time warping pp. 2719-2731

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

Latent multinomial models for extended batch‐mark data pp. 2732-2742

Wei Zhang, Simon J. Bonner and Rachel S. McCrea

A sensitivity analysis approach for the causal hazard ratio in randomized and observational studies pp. 2743-2756

Rachel Axelrod and Daniel Nevo

Hospital profiling using Bayesian decision theory pp. 2757-2769

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

Probability and random variables: theory and applications By Iickho Song, So Ryoung Park, Seokho Yoon (2022). Springer Cham. ISBN: 978‐3‐030‐97678‐1; 978‐3‐030‐97679‐8 (eBook). https://doi.org/10.1007/978‐3‐030‐97679‐8 pp. 2770-2770

Chen‐Po Liao

Mendelian randomization: methods for causal inference using genetic variants 2nd edition By Stephen Burgess and Simon G. Thompson. New York: Chapman & Hall. https://doi.org/10.1201/9780429324352 pp. 2771-2772

Chia‐Yen Chen

Fundamentals of high‐dimensional statistics: with exercises and R Labs By Johannes Lederer, Springer International Publishing, 2021. pp. 355. ISBN: 978‐3‐030‐73791‐7 pp. 2772-2773

Li‐Pang Chen

Volume 79, issue 2, 2023

Instrumental variable estimation of the causal hazard ratio pp. 539-550

Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen and Stijn Vansteelandt

Discussion on “Instrumental variable estimation of the causal hazard ratio,” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, Stijn Vansteelandt pp. 551-553

Brigham Russell Frandsen

Discussion on “Instrumental variable estimation of the causal hazard ratio,” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt pp. 554-558

Benjamin R. Baer, Robert L. Strawderman and Ashkan Ertefaie

Discussion on “Instrumental variable estimation of the causal hazard ratio” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt pp. 559-563

A. James O'Malley, Pablo Martínez‐Camblor and Todd A. MacKenzie

Rejoinder to discussions on “Instrumental variable estimation of the causal hazard ratio” pp. 564-568

Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen and Stijn Vansteelandt

Instrumented difference‐in‐differences pp. 569-581

Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy and Dylan S. Small

Discussion on “Instrumented difference‐in‐differences” by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy, and Dylan S. Small pp. 582-586

Jad Beyhum, Jean‐Pierre Florens and Ingrid Van Keilegom

Discussion on “Instrumented difference‐in‐differences” by Ye, Ertefaie, Flory, Hennessy, Small pp. 587-591

Zhiqiang Tan

Discussion on “Instrumented difference‐in‐differences” by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy & Dylan S. Small pp. 592-596

Hyunseung Kang

Discussion on: Instrumented difference‐in‐differences, by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy and Dylan S. Small pp. 597-600

Karla DiazOrdaz

Rejoinder to “Instrumented difference‐in‐differences” pp. 601-603

Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy and Dylan S. Small

A novel Bayesian functional spatial partitioning method with application to prostate cancer lesion detection using MRI pp. 604-615

Maria Masotti, Lin Zhang, Ethan Leng, Gregory J. Metzger and Joseph S. Koopmeiners

Bayesian spatiotemporal modeling on complex‐valued fMRI signals via kernel convolutions pp. 616-628

Cheng‐Han Yu, Raquel Prado, Hernando Ombao and Daniel Rowe

Bayesian inference for stationary points in Gaussian process regression models for event‐related potentials analysis pp. 629-641

Cheng‐Han Yu, Meng Li, Colin Noe, Simon Fischer‐Baum and Marina Vannucci

Bayes optimal informer sets for early‐stage drug discovery pp. 642-654

Peng Yu, Spencer Ericksen, Anthony Gitter and Michael A. Newton

Bayesian interaction selection model for multimodal neuroimaging data analysis pp. 655-668

Yize Zhao, Ben Wu and Jian Kang

Bayesian sample size determination using commensurate priors to leverage preexperimental data pp. 669-683

Haiyan Zheng, Thomas Jaki and James M.S. Wason

Robust Bayesian variable selection for gene–environment interactions pp. 684-694

Jie Ren, Fei Zhou, Xiaoxi Li, Shuangge Ma, Yu Jiang and Cen Wu

Semiparametric additive time‐varying coefficients model for longitudinal data with censored time origin pp. 695-710

Yanqing Sun, Qiong Shou, Peter B. Gilbert, Fei Heng and Xiyuan Qian

Neural networks for clustered and longitudinal data using mixed effects models pp. 711-721

Francesca Mandel, Riddhi Pratim Ghosh and Ian Barnett

Functional data analysis for longitudinal data with informative observation times pp. 722-733

Caleb Weaver, Luo Xiao and Wenbin Lu

A time‐heterogeneous D‐vine copula model for unbalanced and unequally spaced longitudinal data pp. 734-746

Md Erfanul Hoque, Elif F. Acar and Mahmoud Torabi

Multikink quantile regression for longitudinal data with application to progesterone data analysis pp. 747-760

Chuang Wan, Wei Zhong, Wenyang Zhang and Changliang Zou

Model‐based clustering of high‐dimensional longitudinal data via regularization pp. 761-774

Luoying Yang and Tong Tong Wu

Coherent modeling of longitudinal causal effects on binary outcomes pp. 775-787

Linbo Wang, Xiang Meng, Thomas S. Richardson and James M. Robins

Robust approach to combining multiple markers to improve surrogacy pp. 788-798

Xuan Wang, Layla Parast, Larry Han, Lu Tian and Tianxi Cai

Testing for heterogeneity in the utility of a surrogate marker pp. 799-810

Layla Parast, Tianxi Cai and Lu Tian

Selective prediction‐set models with coverage rate guarantees pp. 811-825

Jean Feng, Arjun Sondhi, Jessica Perry and Noah Simon

A joint fairness model with applications to risk predictions for underrepresented populations pp. 826-840

Hyungrok Do, Shinjini Nandi, Preston Putzel, Padhraic Smyth and Judy Zhong

Cross‐trait prediction accuracy of summary statistics in genome‐wide association studies pp. 841-853

Bingxin Zhao, Fei Zou and Hongtu Zhu

Estimating cell type composition using isoform expression one gene at a time pp. 854-865

Hillary M. Heiling, Douglas R. Wilson, Naim U. Rashid, Wei Sun and Joseph G. Ibrahim

Multisource single‐cell data integration by MAW barycenter for Gaussian mixture models pp. 866-877

Lin Lin, Wei Shi, Jianbo Ye and Jia Li

Feature screening with latent responses pp. 878-890

Congran Yu, Wenwen Guo, Xinyuan Song and Hengjian Cui

An eigenvalue ratio approach to inferring population structure from whole genome sequencing data pp. 891-902

Yuyang Xu, Zhonghua Liu and Jianfeng Yao

Ultra‐high dimensional variable selection for doubly robust causal inference pp. 903-914

Dingke Tang, Dehan Kong, Wenliang Pan and Linbo Wang

Joint gene network construction by single‐cell RNA sequencing data pp. 915-925

Meichen Dong, Yiping He, Yuchao Jiang and Fei Zou

Screening methods for linear errors‐in‐variables models in high dimensions pp. 926-939

Linh H. Nghiem, Francis K.C. Hui, Samuel Müller and A.H. Welsh

Clustering high‐dimensional data via feature selection pp. 940-950

Tianqi Liu, Yu Lu, Biqing Zhu and Hongyu Zhao

A general framework of nonparametric feature selection in high‐dimensional data pp. 951-963

Hang Yu, Yuanjia Wang and Donglin Zeng

Random projection ensemble classification with high‐dimensional time series pp. 964-974

Fuli Zhang and Kung‐Sik Chan

Estimation of the odds ratio in a proportional odds model with censored time‐lagged outcome in a randomized clinical trial pp. 975-987

Anastasios A. Tsiatis, Marie Davidian and Shannon T. Holloway

Variable selection in regression‐based estimation of dynamic treatment regimes pp. 988-999

Zeyu Bian, Erica E. M. Moodie, Susan M. Shortreed and Sahir Bhatnagar

Nonparametric and semiparametric estimation with sequentially truncated survival data pp. 1000-1013

Rebecca A. Betensky, Jing Qian and Jingyao Hou

Nonparametric estimation of the causal effect of a stochastic threshold‐based intervention pp. 1014-1028

Lars van der Laan, Wenbo Zhang and Peter B. Gilbert

Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso pp. 1029-1041

Ashkan Ertefaie, Nima S. Hejazi and Mark J. van der Laan

Posttreatment confounding in causal mediation studies: A cutting‐edge problem and a novel solution via sensitivity analysis pp. 1042-1056

Guanglei Hong, Fan Yang and Xu Qin

Efficient and robust methods for causally interpretable meta‐analysis: Transporting inferences from multiple randomized trials to a target population pp. 1057-1072

Issa J. Dahabreh, Sarah E. Robertson, Lucia C. Petito, Miguel A. Hernán and Jon A. Steingrimsson

Generalized network structured models with mixed responses subject to measurement error and misclassification pp. 1073-1088

Qihuang Zhang and Grace Y. Yi

Zero‐inflated Poisson models with measurement error in the response pp. 1089-1102

Qihuang Zhang and Grace Y. Yi

Closed testing with Globaltest, with application in metabolomics pp. 1103-1113

Ningning Xu, Aldo Solari and Jelle J. Goeman

A note on familywise error rate for a primary and secondary endpoint pp. 1114-1118

Michael A. Proschan and Dean A. Follmann

Domain selection and familywise error rate for functional data: A unified framework pp. 1119-1132

Konrad Abramowicz, Alessia Pini, Lina Schelin, Sara Sjöstedt de Luna, Aymeric Stamm and Simone Vantini

Exact‐corrected confidence interval for risk difference in noninferiority binomial trials pp. 1133-1144

Nour Hawila and Arthur Berg

Estimated quadratic inference function for correlated failure time data pp. 1145-1158

Feifei Yan, Yanyan Liu, Jianwen Cai and Haibo Zhou

The generalized Fisher's combination and accurate p‐value calculation under dependence pp. 1159-1172

Hong Zhang and Zheyang Wu

Inference for nonparanormal partial correlation via regularized rank‐based nodewise regression pp. 1173-1186

Haoyan Hu and Yumou Qiu

Decomposition of variation of mixed variables by a latent mixed Gaussian copula model pp. 1187-1200

Yutong Liu, Toni Darville, Xiaojing Zheng and Quefeng Li

A compound decision approach to covariance matrix estimation pp. 1201-1212

Huiqin Xin and Sihai Dave Zhao

Improving trial generalizability using observational studies pp. 1213-1225

Dasom Lee, Shu Yang, Lin Dong, Xiaofei Wang, Donglin Zeng and Jianwen Cai

Functional group bridge for simultaneous regression and support estimation pp. 1226-1238

Zhengjia Wang, John Magnotti, Michael S. Beauchamp and Meng Li

Robust functional principal component analysis via a functional pairwise spatial sign operator pp. 1239-1253

Guangxing Wang, Sisheng Liu, Fang Han and Chong‐Zhi Di

Continuous time‐interaction processes for population size estimation, with an application to drug dealing in Italy pp. 1254-1267

Linda Altieri, Alessio Farcomeni and Danilo Alunni Fegatelli

Score test for missing at random or not under logistic missingness models pp. 1268-1279

Hairu Wang, Zhiping Lu and Yukun Liu

A cross‐validation statistical framework for asymmetric data integration pp. 1280-1292

Lam Tran, Kevin He, Di Wang and Hui Jiang

Power analysis for cluster randomized trials with continuous coprimary endpoints pp. 1293-1305

Siyun Yang, Mirjam Moerbeek, Monica Taljaard and Fan Li

Translocation detection from Hi‐C data via scan statistics pp. 1306-1317

Anthony Cheng, Disheng Mao, Yuping Zhang, Joseph Glaz and Zhengqing Ouyang

It's all relative: Regression analysis with compositional predictors pp. 1318-1329

Gen Li, Yan Li and Kun Chen

A formal causal interpretation of the case‐crossover design pp. 1330-1343

Zach Shahn, Miguel A. Hernán and James M. Robins

Discussion of “A formal causal interpretation of the case‐crossover design” pp. 1344-1345

Per Kragh Andersen and Torben Martinussen

Discussion of “A formal causal interpretation of the case‐crossover design” by Zach Shahn, Miguel A. Hernan, and James M. Robins pp. 1346-1348

Ruth M. Pfeiffer and Mitchell H. Gail

Discussion on “A formal causal interpretation of the case‐crossover design” by Zach Shahn, Miguel A. Hernán, and James M. Robins pp. 1349-1350

Thomas Lumley

Rejoinder: A formal causal interpretation of the case‐crossover design pp. 1351-1358

Zach Shahn, Miguel A. Hernán and James M. Robins

Supervised two‐dimensional functional principal component analysis with time‐to‐event outcomes and mammogram imaging data pp. 1359-1369

Shu Jiang, Jiguo Cao, Bernard Rosner and Graham A. Colditz

Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data pp. 1370-1382

Laura D'Angelo, Antonio Canale, Zhaoxia Yu and Michele Guindani

Bayesian nonparametric analysis of restricted mean survival time pp. 1383-1396

Chenyang Zhang and Guosheng Yin

A Bayesian functional data model for surveys collected under informative sampling with application to mortality estimation using NHANES pp. 1397-1408

Paul A. Parker and Scott H. Holan

Assessing intervention effects in a randomized trial within a social network pp. 1409-1419

Shaina J. Alexandria, Michael G. Hudgens and Allison E. Aiello

Design and analysis of two‐phase studies with multivariate longitudinal data pp. 1420-1432

Chiara Di Gravio, Ran Tao and Jonathan S. Schildcrout

An alternative metric for evaluating the potential patient benefit of response‐adaptive randomization procedures pp. 1433-1445

Jennifer Proper and Thomas A. Murray

A Bayesian model with application for adaptive platform trials having temporal changes pp. 1446-1458

Chenguang Wang, Min Lin, Gary L. Rosner and Guoxing Soon

A Bayesian platform trial design to simultaneously evaluate multiple drugs in multiple indications with mixed endpoints pp. 1459-1471

Yujie Zhao, Rui (Sammi) Tang, Yeting Du and Ying Yuan

Leveraging a surrogate outcome to improve inference on a partially missing target outcome pp. 1472-1484

Zachary R. McCaw, Sheila M. Gaynor, Ryan Sun and Xihong Lin

A repeated measures approach to pooled and calibrated biomarker data pp. 1485-1495

Abigail Sloan, Chao Cheng, Bernard Rosner, Regina G. Ziegler, Stephanie A. Smith‐Warner and Molin Wang

Evaluating treatment effects in group sequential multivariate longitudinal studies with covariate adjustment pp. 1496-1506

Neal O. Jeffries, James F. Troendle and Nancy L. Geller

A hierarchical model for analyzing multisite individual‐level disease surveillance data from multiple systems pp. 1507-1519

Yuzi Zhang, Howard H. Chang, Qu Cheng, Philip A. Collender, Ting Li, Jinge He and Justin V. Remais

Semiparametric count data regression for self‐reported mental health pp. 1520-1533

Daniel R. Kowal and Bohan Wu

Increasing efficiency and reducing bias when assessing HPV vaccination efficacy by using nontargeted HPV strains pp. 1534-1545

Lola Etievant, Joshua N. Sampson and Mitchell H. Gail

Simplifying the estimation of diagnostic testing accuracy over time for high specificity tests in the absence of a gold standard pp. 1546-1558

Clara Drew, Moses Badio, Dehkontee Dennis, Lisa Hensley, Elizabeth Higgs, Michael Sneller, Mosoka Fallah and Cavan Reilly

Flexible copula model for integrating correlated multi‐omics data from single‐cell experiments pp. 1559-1572

Zichen Ma, Shannon W. Davis and Yen‐Yi Ho

Inference for set‐based effects in genetic association studies with interval‐censored outcomes pp. 1573-1585

Ryan Sun, Liang Zhu, Yimei Li, Yutaka Yasui and Leslie Robison

Statistics in the public interest: In memory of Stephen E. Fienberg Alicia L. Carriquiry, Judith M. Tanur, William F. Eddy, Margaret L. Smykla (Eds.), New York City: Springer. 2022 pp. 1586-1587

David Banks

Writing grant proposals in epidemiology, preventive medicine, and biostatistics Lisa Chasan‐Taber, CRC Press: Boca Raton FL. 2022. https://doi.org/10.1201/9781003155140 pp. 1587-1589

James S. Hodges

Principles of biostatistics (3rd ed) Marcello Pagano, Kimberlee Gauvreau, Heather Mattie (2022). Boca Raton, FL: CRC Press pp. 1589-1590

Chuhsing Kate Hsiao

Volume 79, issue 1, 2023

Adaptive enrichment designs with a continuous biomarker pp. 9-19

Nigel Stallard

Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard pp. 20-22

Rachael V. Phillips and Mark J. van der Laan

Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard pp. 23-25

James M. S. Wason

Discussion on “Adaptive enrichment designs with a continuous biomarker” by N. Stallard pp. 26-30

Christopher Jennison

Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard pp. 31-35

Nancy Flournoy and Sergey Tarima

Rejoinder to discussion on “Adaptive enrichment designs with a continuous biomarker” pp. 36-38

Nigel Stallard

Covariate adjustment in continuous biomarker assessment pp. 39-48

Ziyi Li, Yijian Huang, Dattatraya Patil and Martin G. Sanda

Elastic priors to dynamically borrow information from historical data in clinical trials pp. 49-60

Liyun Jiang, Lei Nie and Ying Yuan

On restricted mean time in favor of treatment pp. 61-72

Lu Mao

Dynamic logistic state space prediction model for clinical decision making pp. 73-85

Jiakun Jiang, Wei Yang, Erin M. Schnellinger, Stephen E. Kimmel and Wensheng Guo

A novel statistical test for treatment differences in clinical trials using a response‐adaptive forward‐looking Gittins Index Rule pp. 86-97

Helen Yvette Barnett, Sofía S. Villar, Helena Geys and Thomas Jaki

Sample size considerations for stepped wedge designs with subclusters pp. 98-112

Kendra Davis‐Plourde, Monica Taljaard and Fan Li

Functional additive models for optimizing individualized treatment rules pp. 113-126

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

Estimation of separable direct and indirect effects in continuous time pp. 127-139

Torben Martinussen and Mats Julius Stensrud

Noniterative adjustment to regression estimators with population‐based auxiliary information for semiparametric models pp. 140-150

Fei Gao and K. C. G. Chan

Bayesian nonparametric quantile process regression and estimation of marginal quantile effects pp. 151-164

Steven G. Xu and Brian J. Reich

Accelerated failure time modeling via nonparametric mixtures pp. 165-177

Byungtae Seo and Sangwook Kang

Jackknife model averaging for high‐dimensional quantile regression pp. 178-189

Miaomiao Wang, Xinyu Zhang, Alan T. K. Wan, Kang You and Guohua Zou

Risk prediction with imperfect survival outcome information from electronic health records pp. 190-202

Jue Hou, Stephanie F. Chan, Xuan Wang and Tianxi Cai

CASANOVA: Permutation inference in factorial survival designs pp. 203-215

Marc Ditzhaus, Jon Genuneit, Arnold Janssen and Markus Pauly

A matching procedure for sequential experiments that iteratively learns which covariates improve power pp. 216-229

Adam Kapelner and Abba Krieger

SMIM: A unified framework of survival sensitivity analysis using multiple imputation and martingale pp. 230-240

Shu Yang, Yilong Zhang, Guanghan Frank Liu and Qian Guan

Logistic regression analysis of two‐phase studies using generalized method of moments pp. 241-252

Prosenjit Kundu and Nilanjan Chatterjee

Instrumental variable estimation of complier causal treatment effect with interval‐censored data pp. 253-263

Shuwei Li and Limin Peng

Integrating sample similarities into latent class analysis: a tree‐structured shrinkage approach pp. 264-279

Mengbing Li, Daniel E. Park, Maliha Aziz, Cindy M. Liu, Lance B. Price and Zhenke Wu

Latent group detection in functional partially linear regression models pp. 280-291

Wu Wang, Ying Sun and Huixia Judy Wang

Variable selection in nonlinear function‐on‐scalar regression pp. 292-303

Rahul Ghosal and Arnab Maity

Spectra in low‐rank localized layers (SpeLLL) for interpretable time–frequency analysis pp. 304-318

Marie Tuft, Martica H. Hall and Robert T. Krafty

Modelling publication bias and p‐hacking pp. 319-331

Jonas Moss and Riccardo De Bin

Generalized case‐control sampling under generalized linear models pp. 332-343

Jacob M. Maronge, Ran Tao, Jonathan S. Schildcrout and Paul J. Rathouz

Debiased lasso for generalized linear models with a diverging number of covariates pp. 344-357

Lu Xia, Bin Nan and Yi Li

Accounting for post‐randomization variables in meta‐analysis: A joint meta‐regression approach pp. 358-367

Qinshu Lian, Jing Zhang, James S. Hodges, Yong Chen and Haitao Chu

Interim monitoring in sequential multiple assignment randomized trials pp. 368-380

Liwen Wu, Junyao Wang and Abdus S. Wahed

Inference in response‐adaptive clinical trials when the enrolled population varies over time pp. 381-393

Massimiliano Russo, Steffen Ventz, Victoria Wang and Lorenzo Trippa

Improving efficiency of inference in clinical trials with external control data pp. 394-403

Xinyu Li, Wang Miao, Fang Lu and Xiao‐Hua Zhou

Human disease clinical treatment network for the elderly: analysis of the medicare inpatient length of stay and readmission data pp. 404-416

Hao Mei, Ruofan Jia, Guanzhong Qiao, Zhenqiu Lin and Shuangge Ma

A linear mixed model to estimate COVID‐19‐induced excess mortality pp. 417-425

Johan Verbeeck, Christel Faes, Thomas Neyens, Niel Hens, Geert Verbeke, Patrick Deboosere and Geert Molenberghs

An individual level infectious disease model in the presence of uncertainty from multiple, imperfect diagnostic tests pp. 426-436

Caitlin Ward, Grant D. Brown and Jacob J. Oleson

A smoothed corrected score approach for proportional hazards model with misclassified discretized covariates induced by error‐contaminated continuous time‐dependent exposure pp. 437-448

Xiao Song, Edward C. Chao and Ching‐Yun Wang

Estimating perinatal critical windows of susceptibility to environmental mixtures via structured Bayesian regression tree pairs pp. 449-461

Daniel Mork and Ander Wilson

Bayesian multiple index models for environmental mixtures pp. 462-474

Glen McGee, Ander Wilson, Thomas F. Webster and Brent A. Coull

Sensitivity analyses informed by tests for bias in observational studies pp. 475-487

Paul R. Rosenbaum

Evaluating the association between latent classes and competing risks outcomes with multiphenotype data pp. 488-501

Teng Fei, John Hanfelt and Limin Peng

Causal inference with outcomes truncated by death in multiarm studies pp. 502-513

Shanshan Luo, Wei Li and Yangbo He

Reader reaction to “Outcome‐adaptive lasso: Variable selection for causal inference” by Shortreed and Ertefaie (2017) pp. 514-520

Ismaila Baldé, Yi Archer Yang and Geneviève Lefebvre

Rejoinder to “Reader reaction to ‘Outcome‐adaptive Lasso: Variable selection for causal inference’ by Shortreed and Ertefaie (2017)” pp. 521-525

Jeremiah Jones, Ashkan Ertefaie and Susan M. Shortreed

Gene expression data analysis: a statistical and machine learning perspective. Pankaj Barah, Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita (2022). Boca Raton, Florida and London. CRC Press; Taylor and Francis. https://doi.org/10.1201/9780429322655 pp. 526-528

Amrita Chattopadhyay

Confidence intervals for discrete data in clinical research By Vivek Pradhan, Ashis K. Gangopadhyay, Sandeep M. Menon, Cynthia Basu, Tathagata Banerjee, Chapman and Hall. 2021. pp. 226. $119.95. (hbk). ISBN: 978‐1138048980 pp. 528-531

Naitee Ting

The effect: An introduction to research design and causality By Nick Huntington‐Klein (2022). New York. Chapman and Hall. https://doi.org/10.1201/9781003226055 pp. 531-532

Hung‐Ching Chang and Michael T. Gorczyca