Content
September 2023, Volume 79, Issue 3
- 1597-1609 Structural cumulative survival models for estimation of treatment effects accounting for treatment switching in randomized experiments
by Andrew Ying & Eric J. Tchetgen Tchetgen - 1610-1623 Dimension reduction for integrative survival analysis
by Aaron J. Molstad & Rohit K. Patra - 1624-1634 Concordance indices with left‐truncated and right‐censored data
by Nicholas Hartman & Sehee Kim & Kevin He & John D. Kalbfleisch - 1635-1645 Joint inference for competing risks data using multiple endpoints
by Jiyang Wen & Chen Hu & Mei‐Cheng Wang - 1646-1656 Maximum likelihood estimation in the additive hazards model
by Chengyuan Lu & Jelle Goeman & Hein Putter - 1657-1669 Penalized estimation of frailty‐based illness–death models for semi‐competing risks
by Harrison T. Reeder & Junwei Lu & Sebastien Haneuse - 1670-1685 Marginal proportional hazards models for clustered interval‐censored data with time‐dependent covariates
by Kaitlyn Cook & Wenbin Lu & Rui Wang - 1686-1700 Improved semiparametric estimation of the proportional rate model with recurrent event data
by Ming‐Yueh Huang & Chiung‐Yu Huang - 1701-1712 Non‐parametric estimation of the age‐at‐onset distribution from a cross‐sectional sample
by S. Mandal & J. Qin & R.M. Pfeiffer - 1713-1725 An information ratio‐based goodness‐of‐fit test for copula models on censored data
by Tao Sun & Yu Cheng & Ying Ding - 1726-1736 Model uncertainty quantification in Cox regression
by Gonzalo García‐Donato & Stefano Cabras & María Eugenia Castellanos - 1737-1748 General independent censoring in event‐driven trials with staggered entry
by Jasmin Rühl & Jan Beyersmann & Sarah Friedrich - 1749-1760 Nonparametric inference of general while‐alive estimands for recurrent events
by Lu Mao - 1761-1774 Two‐level Bayesian interaction analysis for survival data incorporating pathway information
by Xing Qin & Shuangge Ma & Mengyun Wu - 1775-1787 A Bayesian multivariate mixture model for high throughput spatial transcriptomics
by Carter Allen & Yuzhou Chang & Brian Neelon & Won Chang & Hang J. Kim & Zihai Li & Qin Ma & Dongjun Chung - 1788-1800 Tractable Bayes of skew‐elliptical link models for correlated binary data
by Zhongwei Zhang & Reinaldo B. Arellano‐Valle & Marc G. Genton & Raphaël Huser - 1801-1813 Integrative Bayesian models using Post‐selective inference: A case study in radiogenomics
by Snigdha Panigrahi & Shariq Mohammed & Arvind Rao & Veerabhadran Baladandayuthapani - 1814-1825 Bayesian regression analysis of skewed tensor responses
by Inkoo Lee & Debajyoti Sinha & Qing Mai & Xin Zhang & Dipankar Bandyopadhyay - 1826-1839 Adaptive Bayesian sum of trees model for covariate‐dependent spectral analysis
by Yakun Wang & Zeda Li & Scott A. Bruce - 1840-1852 Solutions for surrogacy validation with longitudinal outcomes for a gene therapy
by Emily K. Roberts & Michael R. Elliott & Jeremy M. G. Taylor - 1853-1867 Subset selection for linear mixed models
by Daniel R. Kowal - 1868-1879 Grouped generalized estimating equations for longitudinal data analysis
by Tsubasa Ito & Shonosuke Sugasawa - 1880-1895 Asynchronous functional linear regression models for longitudinal data in reproducing kernel Hilbert space
by Ting Li & Huichen Zhu & Tengfei Li & Hongtu Zhu - 1896-1907 Contrasting principal stratum and hypothetical strategy estimands in multi‐period crossover trials with incomplete data
by John N.S. Matthews & Sofia Bazakou & Robin Henderson & Linda D. Sharples - 1908-1919 Optimal multiple testing and design in clinical trials
by Ruth Heller & Abba Krieger & Saharon Rosset - 1920-1933 Change‐plane analysis for subgroup detection with a continuous treatment
by Peng Jin & Wenbin Lu & Yu Chen & Mengling Liu - 1934-1946 Efficient targeted learning of heterogeneous treatment effects for multiple subgroups
by Waverly Wei & Maya Petersen & Mark J van der Laan & Zeyu Zheng & Chong Wu & Jingshen Wang - 1947-1958 Tensor response quantile regression with neuroimaging data
by Bo Wei & Limin Peng & Ying Guo & Amita Manatunga & Jennifer Stevens - 1959-1971 Joint semiparametric models for case‐cohort designs
by Weibin Zhong & Guoqing Diao - 1972-1985 Multidimensional adaptive P‐splines with application to neurons' activity studies
by María Xosé Rodríguez‐Álvarez & María Durbán & Paul H.C. Eilers & Dae‐Jin Lee & Francisco Gonzalez - 1986-1995 Combining parametric and nonparametric models to estimate treatment effects in observational studies
by Daniel Daly‐Grafstein & Paul Gustafson - 1996-2009 Semiparametric estimation of the transformation model by leveraging external aggregate data in the presence of population heterogeneity
by Yu‐Jen Cheng & Yen‐Chun Liu & Chang‐Yu Tsai & Chiung‐Yu Huang - 2010-2022 A semiparametric joint model for cluster size and subunit‐specific interval‐censored outcomes
by Chun Yin Lee & Kin Yau Wong & Kwok Fai Lam & Dipankar Bandyopadhyay - 2023-2035 A robust approach for electronic health record–based case‐control studies with contaminated case pools
by Guorong Dai & Yanyuan Ma & Jill Hasler & Jinbo Chen & Raymond J. Carroll - 2036-2049 Quantile regression for nonignorable missing data with its application of analyzing electronic medical records
by Aiai Yu & Yujie Zhong & Xingdong Feng & Ying Wei - 2050-2062 Frequentist model averaging for undirected Gaussian graphical models
by Huihang Liu & Xinyu Zhang - 2063-2075 Nonparametric scanning tests of homogeneity for hierarchical models with continuous covariates
by David Todem & Wei‐Wen Hsu & KyungMann Kim - 2076-2088 Identifying alert concentrations using a model‐based bootstrap approach
by Kathrin Möllenhoff & Kirsten Schorning & Franziska Kappenberg - 2089-2102 Adjusting for publication bias in meta‐analysis via inverse probability weighting using clinical trial registries
by Ao Huang & Kosuke Morikawa & Tim Friede & Satoshi Hattori - 2103-2115 Elastic analysis of irregularly or sparsely sampled curves
by Lisa Steyer & Almond Stöcker & Sonja Greven - 2116-2126 A general framework for subgroup detection via one‐step value difference estimation
by Dana Johnson & Wenbin Lu & Marie Davidian - 2127-2142 Pair‐switching rerandomization
by Ke Zhu & Hanzhong Liu - 2143-2156 Double reduction estimation and equilibrium tests in natural autopolyploid populations
by David Gerard - 2157-2170 Center‐augmented ℓ2‐type regularization for subgroup learning
by Ye He & Ling Zhou & Yingcun Xia & Huazhen Lin - 2171-2183 A general modeling framework for open wildlife populations based on the Polya tree prior
by Alex Diana & Eleni Matechou & Jim Griffin & Todd Arnold & Simone Tenan & Stefano Volponi - 2184-2195 A novel penalized inverse‐variance weighted estimator for Mendelian randomization with applications to COVID‐19 outcomes
by Siqi Xu & Peng Wang & Wing Kam Fung & Zhonghua Liu - 2196-2207 Testing weak nulls in matched observational studies
by Colin B. Fogarty - 2208-2219 Mendelian randomization mixed‐scale treatment effect robust identification and estimation for causal inference
by Zhonghua Liu & Ting Ye & Baoluo Sun & Mary Schooling & Eric Tchetgen Tchetgen - 2220-2231 Generalized propensity score approach to causal inference with spatial interference
by A. Giffin & B. J. Reich & S. Yang & A. G. Rappold - 2232-2245 Functional data analysis with covariate‐dependent mean and covariance structures
by Chenlin Zhang & Huazhen Lin & Li Liu & Jin Liu & Yi Li - 2246-2259 Simultaneous cluster structure learning and estimation of heterogeneous graphs for matrix‐variate fMRI data
by Dong Liu & Changwei Zhao & Yong He & Lei Liu & Ying Guo & Xinsheng Zhang - 2260-2271 Estimating tree‐based dynamic treatment regimes using observational data with restricted treatment sequences
by Nina Zhou & Lu Wang & Daniel Almirall - 2272-2285 Segmented correspondence curve regression for quantifying covariate effects on the reproducibility of high‐throughput experiments
by Feipeng Zhang & Qunhua Li - 2286-2297 Concave likelihood‐based regression with finite‐support response variables
by K.O. Ekvall & M. Bottai - 2298-2310 Boosting distributional copula regression
by Nicolai Hans & Nadja Klein & Florian Faschingbauer & Michael Schneider & Andreas Mayr - 2311-2320 On generalized latent factor modeling and inference for high‐dimensional binomial data
by Ting Fung Ma & Fangfang Wang & Jun Zhu - 2321-2332 Microbiome subcommunity learning with logistic‐tree normal latent Dirichlet allocation
by Patrick LeBlanc & Li Ma - 2333-2345 Identifying brain hierarchical structures associated with Alzheimer's disease using a regularized regression method with tree predictors
by Yi Zhao & Bingkai Wang & Chin‐Fu Liu & Andreia V. Faria & Michael I. Miller & Brian S. Caffo & Xi Luo - 2346-2356 How well can fine balance work for covariate balancing
by Ruoqi Yu - 2357-2369 CEDAR: communication efficient distributed analysis for regressions
by Changgee Chang & Zhiqi Bu & Qi Long - 2370-2381 Statistical inference and power analysis for direct and spillover effects in two‐stage randomized experiments
by Zhichao Jiang & Kosuke Imai & Anup Malani - 2382-2393 Estimating the area under the ROC curve when transporting a prediction model to a target population
by Bing Li & Constantine Gatsonis & Issa J. Dahabreh & Jon A. Steingrimsson - 2394-2403 Inference for the dimension of a regression relationship using pseudo‐covariates
by Shih‐Hao Huang & Kerby Shedden & Hsin‐wen Chang - 2404-2416 Consistent estimation of the number of communities via regularized network embedding
by Mingyang Ren & Sanguo Zhang & Junhui Wang - 2417-2429 Automated analysis of low‐field brain MRI in cerebral malaria
by 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 & Russell T. Shinohara - 2430-2443 A high‐dimensional mediation model for a neuroimaging mediator: Integrating clinical, neuroimaging, and neurocognitive data to mitigate late effects in pediatric cancer
by Jade Xiaoqing Wang & Yimei Li & Wilburn E. Reddick & Heather M. Conklin & John O. Glass & Arzu Onar‐Thomas & Amar Gajjar & Cheng Cheng & Zhao‐Hua Lu - 2444-2457 A latent state space model for estimating brain dynamics from electroencephalogram (EEG) data
by Qinxia Wang & Ji Meng Loh & Xiaofu He & Yuanjia Wang - 2458-2473 Bayesian treatment screening and selection using subgroup‐specific utilities of response and toxicity
by Juhee Lee & Peter F. Thall & Pavlos Msaouel - 2474-2488 Bayesian hierarchical quantile regression with application to characterizing the immune architecture of lung cancer
by Priyam Das & Christine B. Peterson & Yang Ni & Alexandre Reuben & Jiexin Zhang & Jianjun Zhang & Kim‐Anh Do & Veerabhadran Baladandayuthapani - 2489-2502 Bayesian sample size calculations for comparing two strategies in SMART studies
by Armando Turchetta & Erica E. M. Moodie & David A. Stephens & Sylvie D. Lambert - 2503-2515 Fast Bayesian inference for large occupancy datasets
by Alex Diana & Emily Beth Dennis & Eleni Matechou & Byron John Treharne Morgan - 2516-2524 Comparing COVID‐19 incidences longitudinally per economic sector against the background of preventive measures and vaccination
by Florian Stijven & Johan Verbeeck & Geert Molenberghs - 2525-2536 Age‐related model for estimating the symptomatic and asymptomatic transmissibility of COVID‐19 patients
by Jianbin Tan & Ye Shen & Yang Ge & Leonardo Martinez & Hui Huang - 2537-2550 Correcting delayed reporting of COVID‐19 using the generalized‐Dirichlet‐multinomial method
by Oliver Stoner & Alba Halliday & Theo Economou - 2551-2564 Assessing exposure‐time treatment effect heterogeneity in stepped‐wedge cluster randomized trials
by Lara Maleyeff & Fan Li & Sebastien Haneuse & Rui Wang - 2565-2576 Design considerations for two‐stage enrichment clinical trials
by Rosamarie Frieri & William Fisher Rosenberger & Nancy Flournoy & Zhantao Lin - 2577-2591 Efficient and robust approaches for analysis of sequential multiple assignment randomized trials: Illustration using the ADAPT‐R trial
by Lina M. Montoya & Michael R. Kosorok & Elvin H. Geng & Joshua Schwab & Thomas A. Odeny & Maya L. Petersen - 2592-2604 Infinite hidden Markov models for multiple multivariate time series with missing data
by Lauren Hoskovec & Matthew D. Koslovsky & Kirsten Koehler & Nicholas Good & Jennifer L. Peel & John Volckens & Ander Wilson - 2605-2618 Spatial dependence modeling of latent susceptibility and time to joint damage in psoriatic arthritis
by Fangya Mao & Richard J. Cook - 2619-2632 Semiparametric distributed lag quantile regression for modeling time‐dependent exposure mixtures
by Yuyan Wang & Akhgar Ghassabian & Bo Gu & Yelena Afanasyeva & Yiwei Li & Leonardo Trasande & Mengling Liu - 2633-2648 Misdiagnosis‐related harm quantification through mixture models and harm measures
by Yuxin Zhu & Zheyu Wang & David Newman‐Toker - 2649-2663 Multiwave validation sampling for error‐prone electronic health records
by Bryan E. Shepherd & Kyunghee Han & Tong Chen & Aihua Bian & Shannon Pugh & Stephany N. Duda & Thomas Lumley & William J. Heerman & Pamela A. Shaw - 2664-2676 Prioritizing candidate peptides for cancer vaccines through predicting peptide presentation by HLA‐I proteins
by Laura Y. Zhou & Fei Zou & Wei Sun - 2677-2690 Neural network on interval‐censored data with application to the prediction of Alzheimer's disease
by Tao Sun & Ying Ding - 2691-2704 Delivering spatially comparable inference on the risks of multiple severities of respiratory disease from spatially misaligned disease count data
by Duncan Lee & Craig Anderson - 2705-2718 Associating somatic mutation with clinical outcomes through kernel regression and optimal transport
by Paul Little & Li Hsu & Wei Sun - 2719-2731 Pattern‐based clustering of daily weigh‐in trajectories using dynamic time warping
by Samantha Bothwell & Alex Kaizer & Ryan Peterson & Danielle Ostendorf & Victoria Catenacci & Julia Wrobel - 2732-2742 Latent multinomial models for extended batch‐mark data
by Wei Zhang & Simon J. Bonner & Rachel S. McCrea - 2743-2756 A sensitivity analysis approach for the causal hazard ratio in randomized and observational studies
by Rachel Axelrod & Daniel Nevo - 2757-2769 Hospital profiling using Bayesian decision theory
by Johannes Hengelbrock & Johannes Rauh & Jona Cederbaum & Maximilian Kähler & Michael Höhle - 2770-2770 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
by Chen‐Po Liao - 2771-2772 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
by Chia‐Yen Chen - 2772-2773 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
by Li‐Pang Chen
June 2023, Volume 79, Issue 2
- 539-550 Instrumental variable estimation of the causal hazard ratio
by Linbo Wang & Eric Tchetgen Tchetgen & Torben Martinussen & Stijn Vansteelandt - 551-553 Discussion on “Instrumental variable estimation of the causal hazard ratio,” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, Stijn Vansteelandt
by Brigham Russell Frandsen - 554-558 Discussion on “Instrumental variable estimation of the causal hazard ratio,” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt
by Benjamin R. Baer & Robert L. Strawderman & Ashkan Ertefaie - 559-563 Discussion on “Instrumental variable estimation of the causal hazard ratio” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt
by A. James O'Malley & Pablo Martínez‐Camblor & Todd A. MacKenzie - 564-568 Rejoinder to discussions on “Instrumental variable estimation of the causal hazard ratio”
by Linbo Wang & Eric Tchetgen Tchetgen & Torben Martinussen & Stijn Vansteelandt - 569-581 Instrumented difference‐in‐differences
by Ting Ye & Ashkan Ertefaie & James Flory & Sean Hennessy & Dylan S. Small - 582-586 Discussion on “Instrumented difference‐in‐differences” by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy, and Dylan S. Small
by Jad Beyhum & Jean‐Pierre Florens & Ingrid Van Keilegom - 587-591 Discussion on “Instrumented difference‐in‐differences” by Ye, Ertefaie, Flory, Hennessy, Small
by Zhiqiang Tan - 592-596 Discussion on “Instrumented difference‐in‐differences” by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy & Dylan S. Small
by Hyunseung Kang - 597-600 Discussion on: Instrumented difference‐in‐differences, by Ting Ye, Ashkan Ertefaie, James Flory, Sean Hennessy and Dylan S. Small
by Karla DiazOrdaz - 601-603 Rejoinder to “Instrumented difference‐in‐differences”
by Ting Ye & Ashkan Ertefaie & James Flory & Sean Hennessy & Dylan S. Small - 604-615 A novel Bayesian functional spatial partitioning method with application to prostate cancer lesion detection using MRI
by Maria Masotti & Lin Zhang & Ethan Leng & Gregory J. Metzger & Joseph S. Koopmeiners - 616-628 Bayesian spatiotemporal modeling on complex‐valued fMRI signals via kernel convolutions
by Cheng‐Han Yu & Raquel Prado & Hernando Ombao & Daniel Rowe - 629-641 Bayesian inference for stationary points in Gaussian process regression models for event‐related potentials analysis
by Cheng‐Han Yu & Meng Li & Colin Noe & Simon Fischer‐Baum & Marina Vannucci - 642-654 Bayes optimal informer sets for early‐stage drug discovery
by Peng Yu & Spencer Ericksen & Anthony Gitter & Michael A. Newton - 655-668 Bayesian interaction selection model for multimodal neuroimaging data analysis
by Yize Zhao & Ben Wu & Jian Kang - 669-683 Bayesian sample size determination using commensurate priors to leverage preexperimental data
by Haiyan Zheng & Thomas Jaki & James M.S. Wason - 684-694 Robust Bayesian variable selection for gene–environment interactions
by Jie Ren & Fei Zhou & Xiaoxi Li & Shuangge Ma & Yu Jiang & Cen Wu - 695-710 Semiparametric additive time‐varying coefficients model for longitudinal data with censored time origin
by Yanqing Sun & Qiong Shou & Peter B. Gilbert & Fei Heng & Xiyuan Qian - 711-721 Neural networks for clustered and longitudinal data using mixed effects models
by Francesca Mandel & Riddhi Pratim Ghosh & Ian Barnett - 722-733 Functional data analysis for longitudinal data with informative observation times
by Caleb Weaver & Luo Xiao & Wenbin Lu - 734-746 A time‐heterogeneous D‐vine copula model for unbalanced and unequally spaced longitudinal data
by Md Erfanul Hoque & Elif F. Acar & Mahmoud Torabi - 747-760 Multikink quantile regression for longitudinal data with application to progesterone data analysis
by Chuang Wan & Wei Zhong & Wenyang Zhang & Changliang Zou - 761-774 Model‐based clustering of high‐dimensional longitudinal data via regularization
by Luoying Yang & Tong Tong Wu - 775-787 Coherent modeling of longitudinal causal effects on binary outcomes
by Linbo Wang & Xiang Meng & Thomas S. Richardson & James M. Robins - 788-798 Robust approach to combining multiple markers to improve surrogacy
by Xuan Wang & Layla Parast & Larry Han & Lu Tian & Tianxi Cai - 799-810 Testing for heterogeneity in the utility of a surrogate marker
by Layla Parast & Tianxi Cai & Lu Tian - 811-825 Selective prediction‐set models with coverage rate guarantees
by Jean Feng & Arjun Sondhi & Jessica Perry & Noah Simon - 826-840 A joint fairness model with applications to risk predictions for underrepresented populations
by Hyungrok Do & Shinjini Nandi & Preston Putzel & Padhraic Smyth & Judy Zhong - 841-853 Cross‐trait prediction accuracy of summary statistics in genome‐wide association studies
by Bingxin Zhao & Fei Zou & Hongtu Zhu - 854-865 Estimating cell type composition using isoform expression one gene at a time
by Hillary M. Heiling & Douglas R. Wilson & Naim U. Rashid & Wei Sun & Joseph G. Ibrahim - 866-877 Multisource single‐cell data integration by MAW barycenter for Gaussian mixture models
by Lin Lin & Wei Shi & Jianbo Ye & Jia Li - 878-890 Feature screening with latent responses
by Congran Yu & Wenwen Guo & Xinyuan Song & Hengjian Cui - 891-902 An eigenvalue ratio approach to inferring population structure from whole genome sequencing data
by Yuyang Xu & Zhonghua Liu & Jianfeng Yao - 903-914 Ultra‐high dimensional variable selection for doubly robust causal inference
by Dingke Tang & Dehan Kong & Wenliang Pan & Linbo Wang - 915-925 Joint gene network construction by single‐cell RNA sequencing data
by Meichen Dong & Yiping He & Yuchao Jiang & Fei Zou - 926-939 Screening methods for linear errors‐in‐variables models in high dimensions
by Linh H. Nghiem & Francis K.C. Hui & Samuel Müller & A.H. Welsh - 940-950 Clustering high‐dimensional data via feature selection
by Tianqi Liu & Yu Lu & Biqing Zhu & Hongyu Zhao - 951-963 A general framework of nonparametric feature selection in high‐dimensional data
by Hang Yu & Yuanjia Wang & Donglin Zeng - 964-974 Random projection ensemble classification with high‐dimensional time series
by Fuli Zhang & Kung‐Sik Chan - 975-987 Estimation of the odds ratio in a proportional odds model with censored time‐lagged outcome in a randomized clinical trial
by Anastasios A. Tsiatis & Marie Davidian & Shannon T. Holloway - 988-999 Variable selection in regression‐based estimation of dynamic treatment regimes
by Zeyu Bian & Erica E. M. Moodie & Susan M. Shortreed & Sahir Bhatnagar - 1000-1013 Nonparametric and semiparametric estimation with sequentially truncated survival data
by Rebecca A. Betensky & Jing Qian & Jingyao Hou - 1014-1028 Nonparametric estimation of the causal effect of a stochastic threshold‐based intervention
by Lars van der Laan & Wenbo Zhang & Peter B. Gilbert - 1029-1041 Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso
by Ashkan Ertefaie & Nima S. Hejazi & Mark J. van der Laan - 1042-1056 Posttreatment confounding in causal mediation studies: A cutting‐edge problem and a novel solution via sensitivity analysis
by Guanglei Hong & Fan Yang & Xu Qin - 1057-1072 Efficient and robust methods for causally interpretable meta‐analysis: Transporting inferences from multiple randomized trials to a target population
by Issa J. Dahabreh & Sarah E. Robertson & Lucia C. Petito & Miguel A. Hernán & Jon A. Steingrimsson - 1073-1088 Generalized network structured models with mixed responses subject to measurement error and misclassification
by Qihuang Zhang & Grace Y. Yi - 1089-1102 Zero‐inflated Poisson models with measurement error in the response
by Qihuang Zhang & Grace Y. Yi - 1103-1113 Closed testing with Globaltest, with application in metabolomics
by Ningning Xu & Aldo Solari & Jelle J. Goeman - 1114-1118 A note on familywise error rate for a primary and secondary endpoint
by Michael A. Proschan & Dean A. Follmann - 1119-1132 Domain selection and familywise error rate for functional data: A unified framework
by Konrad Abramowicz & Alessia Pini & Lina Schelin & Sara Sjöstedt de Luna & Aymeric Stamm & Simone Vantini - 1133-1144 Exact‐corrected confidence interval for risk difference in noninferiority binomial trials
by Nour Hawila & Arthur Berg - 1145-1158 Estimated quadratic inference function for correlated failure time data
by Feifei Yan & Yanyan Liu & Jianwen Cai & Haibo Zhou - 1159-1172 The generalized Fisher's combination and accurate p‐value calculation under dependence
by Hong Zhang & Zheyang Wu - 1173-1186 Inference for nonparanormal partial correlation via regularized rank‐based nodewise regression
by Haoyan Hu & Yumou Qiu - 1187-1200 Decomposition of variation of mixed variables by a latent mixed Gaussian copula model
by Yutong Liu & Toni Darville & Xiaojing Zheng & Quefeng Li - 1201-1212 A compound decision approach to covariance matrix estimation
by Huiqin Xin & Sihai Dave Zhao - 1213-1225 Improving trial generalizability using observational studies
by Dasom Lee & Shu Yang & Lin Dong & Xiaofei Wang & Donglin Zeng & Jianwen Cai - 1226-1238 Functional group bridge for simultaneous regression and support estimation
by Zhengjia Wang & John Magnotti & Michael S. Beauchamp & Meng Li - 1239-1253 Robust functional principal component analysis via a functional pairwise spatial sign operator
by Guangxing Wang & Sisheng Liu & Fang Han & Chong‐Zhi Di - 1254-1267 Continuous time‐interaction processes for population size estimation, with an application to drug dealing in Italy
by Linda Altieri & Alessio Farcomeni & Danilo Alunni Fegatelli - 1268-1279 Score test for missing at random or not under logistic missingness models
by Hairu Wang & Zhiping Lu & Yukun Liu - 1280-1292 A cross‐validation statistical framework for asymmetric data integration
by Lam Tran & Kevin He & Di Wang & Hui Jiang - 1293-1305 Power analysis for cluster randomized trials with continuous coprimary endpoints
by Siyun Yang & Mirjam Moerbeek & Monica Taljaard & Fan Li - 1306-1317 Translocation detection from Hi‐C data via scan statistics
by Anthony Cheng & Disheng Mao & Yuping Zhang & Joseph Glaz & Zhengqing Ouyang - 1318-1329 It's all relative: Regression analysis with compositional predictors
by Gen Li & Yan Li & Kun Chen - 1330-1343 A formal causal interpretation of the case‐crossover design
by Zach Shahn & Miguel A. Hernán & James M. Robins - 1344-1345 Discussion of “A formal causal interpretation of the case‐crossover design”
by Per Kragh Andersen & Torben Martinussen - 1346-1348 Discussion of “A formal causal interpretation of the case‐crossover design” by Zach Shahn, Miguel A. Hernan, and James M. Robins
by Ruth M. Pfeiffer & Mitchell H. Gail - 1349-1350 Discussion on “A formal causal interpretation of the case‐crossover design” by Zach Shahn, Miguel A. Hernán, and James M. Robins
by Thomas Lumley - 1351-1358 Rejoinder: A formal causal interpretation of the case‐crossover design
by Zach Shahn & Miguel A. Hernán & James M. Robins - 1359-1369 Supervised two‐dimensional functional principal component analysis with time‐to‐event outcomes and mammogram imaging data
by Shu Jiang & Jiguo Cao & Bernard Rosner & Graham A. Colditz - 1370-1382 Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data
by Laura D'Angelo & Antonio Canale & Zhaoxia Yu & Michele Guindani - 1383-1396 Bayesian nonparametric analysis of restricted mean survival time
by Chenyang Zhang & Guosheng Yin - 1397-1408 A Bayesian functional data model for surveys collected under informative sampling with application to mortality estimation using NHANES
by Paul A. Parker & Scott H. Holan - 1409-1419 Assessing intervention effects in a randomized trial within a social network
by Shaina J. Alexandria & Michael G. Hudgens & Allison E. Aiello - 1420-1432 Design and analysis of two‐phase studies with multivariate longitudinal data
by Chiara Di Gravio & Ran Tao & Jonathan S. Schildcrout - 1433-1445 An alternative metric for evaluating the potential patient benefit of response‐adaptive randomization procedures
by Jennifer Proper & Thomas A. Murray - 1446-1458 A Bayesian model with application for adaptive platform trials having temporal changes
by Chenguang Wang & Min Lin & Gary L. Rosner & Guoxing Soon - 1459-1471 A Bayesian platform trial design to simultaneously evaluate multiple drugs in multiple indications with mixed endpoints
by Yujie Zhao & Rui (Sammi) Tang & Yeting Du & Ying Yuan - 1472-1484 Leveraging a surrogate outcome to improve inference on a partially missing target outcome
by Zachary R. McCaw & Sheila M. Gaynor & Ryan Sun & Xihong Lin - 1485-1495 A repeated measures approach to pooled and calibrated biomarker data
by Abigail Sloan & Chao Cheng & Bernard Rosner & Regina G. Ziegler & Stephanie A. Smith‐Warner & Molin Wang - 1496-1506 Evaluating treatment effects in group sequential multivariate longitudinal studies with covariate adjustment
by Neal O. Jeffries & James F. Troendle & Nancy L. Geller - 1507-1519 A hierarchical model for analyzing multisite individual‐level disease surveillance data from multiple systems
by Yuzi Zhang & Howard H. Chang & Qu Cheng & Philip A. Collender & Ting Li & Jinge He & Justin V. Remais - 1520-1533 Semiparametric count data regression for self‐reported mental health
by Daniel R. Kowal & Bohan Wu - 1534-1545 Increasing efficiency and reducing bias when assessing HPV vaccination efficacy by using nontargeted HPV strains
by Lola Etievant & Joshua N. Sampson & Mitchell H. Gail - 1546-1558 Simplifying the estimation of diagnostic testing accuracy over time for high specificity tests in the absence of a gold standard
by Clara Drew & Moses Badio & Dehkontee Dennis & Lisa Hensley & Elizabeth Higgs & Michael Sneller & Mosoka Fallah & Cavan Reilly - 1559-1572 Flexible copula model for integrating correlated multi‐omics data from single‐cell experiments
by Zichen Ma & Shannon W. Davis & Yen‐Yi Ho - 1573-1585 Inference for set‐based effects in genetic association studies with interval‐censored outcomes
by Ryan Sun & Liang Zhu & Yimei Li & Yutaka Yasui & Leslie Robison - 1586-1587 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
by David Banks - 1587-1589 Writing grant proposals in epidemiology, preventive medicine, and biostatistics Lisa Chasan‐Taber, CRC Press: Boca Raton FL. 2022. https://doi.org/10.1201/9781003155140
by James S. Hodges - 1589-1590 Principles of biostatistics (3rd ed) Marcello Pagano, Kimberlee Gauvreau, Heather Mattie (2022). Boca Raton, FL: CRC Press
by Chuhsing Kate Hsiao
March 2023, Volume 79, Issue 1
- 9-19 Adaptive enrichment designs with a continuous biomarker
by Nigel Stallard - 20-22 Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard
by Rachael V. Phillips & Mark J. van der Laan - 23-25 Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard
by James M. S. Wason - 26-30 Discussion on “Adaptive enrichment designs with a continuous biomarker” by N. Stallard
by Christopher Jennison - 31-35 Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard
by Nancy Flournoy & Sergey Tarima - 36-38 Rejoinder to discussion on “Adaptive enrichment designs with a continuous biomarker”
by Nigel Stallard - 39-48 Covariate adjustment in continuous biomarker assessment
by Ziyi Li & Yijian Huang & Dattatraya Patil & Martin G. Sanda - 49-60 Elastic priors to dynamically borrow information from historical data in clinical trials
by Liyun Jiang & Lei Nie & Ying Yuan - 61-72 On restricted mean time in favor of treatment
by Lu Mao - 73-85 Dynamic logistic state space prediction model for clinical decision making
by Jiakun Jiang & Wei Yang & Erin M. Schnellinger & Stephen E. Kimmel & Wensheng Guo - 86-97 A novel statistical test for treatment differences in clinical trials using a response‐adaptive forward‐looking Gittins Index Rule
by Helen Yvette Barnett & Sofía S. Villar & Helena Geys & Thomas Jaki - 98-112 Sample size considerations for stepped wedge designs with subclusters
by Kendra Davis‐Plourde & Monica Taljaard & Fan Li - 113-126 Functional additive models for optimizing individualized treatment rules
by Hyung Park & Eva Petkova & Thaddeus Tarpey & R. Todd Ogden