Biometrika

Volume 89 - 112

Current editor(s): Paul Fearnhead

From Biometrika Trust
Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
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Volume 110, issue 4, 2023

Statistical inference for streamed longitudinal data pp. 841-858

Lan Luo, Jingshen Wang and Emily C Hector

Discussion of ‘Statistical inference for streamed longitudinal data’ pp. 859-862

Peter X-K Song and Ling Zhou

Discussion of ‘Statistical inference for streamed longitudinal data’ pp. 863-866

J Wang, H Wang and K Chen

Discussion of ‘Statistical inference for streamed longitudinal data’ pp. 867-869

Yang Ning and Jingyi Duan

Rejoinder: ‘Statistical inference for streamed longitudinal data’ pp. 871-874

Lan Luo, Jingshen Wang and Emily C Hector

Semiparametric counterfactual density estimation pp. 875-896

E H Kennedy, S Balakrishnan and L A Wasserman

Soft calibration for selection bias problems under mixed-effects models pp. 897-911

Chenyin Gao, Shu Yang and Jae Kwang Kim

Targeted optimal treatment regime learning using summary statistics pp. 913-931

J Chu, W Lu and S Yang

Sampling distribution for single-regression Granger causality estimators pp. 933-952

A J Gutknecht and L Barnett

Semiparametric efficient G-estimation with invalid instrumental variables pp. 953-971

B Sun, Z Liu and E J Tchetgen

Proximal mediation analysis pp. 973-987

Oliver Dukes, Ilya Shpitser and Eric J Tchetgen

An instrumental variable method for point processes: generalized Wald estimation based on deconvolution pp. 989-1008

Zhichao Jiang, Shizhe Chen and Peng Ding

Nonparametric estimation of the intensity function of a spatial point process on a Riemannian manifold pp. 1009-1021

S Ward, H S Battey and E A K Cohen

A robust fusion-extraction procedure with summary statistics in the presence of biased sources pp. 1023-1040

Ruoyu Wang, Qihua Wang and Wang Miao

The surrogate index: Combining short-term proxies to estimate long-term treatment effects more rapidly and precisely pp. 1041-1054

Sijia Li and Alex Luedtke

Equivariant estimation of Fréchet means pp. 1055-1076

A McCormack and P D Hoff

-estimation for smooth eigenvectors of matrix-valued functions pp. 1077-1098

Giovanni Motta, Wei Biao Wu and Mohsen Pourahmadi

A subsampling perspective for extending the validity of state-of-the-art bootstraps in the frequency domain pp. 1099-1115

Haihan Yu, Mark S Kaiser and Daniel J Nordman

Ancestor regression in linear structural equation models pp. 1117-1124

C Schultheiss and P Bühlmann

Volume 110, issue 3, 2023

A generalized Bayes framework for probabilistic clustering pp. 559-578

Tommaso Rigon, Amy H Herring and David B Dunson

Optimal design of the Barker proposal and other locally balanced Metropolis–Hastings algorithms pp. 579-595

Jure Vogrinc, Samuel Livingstone and Giacomo Zanella

Splitting strategies for post-selection inference pp. 597-614

D García Rasines and G A Young

On the implied weights of linear regression for causal inference pp. 615-629

Ambarish Chattopadhyay and José R Zubizarreta

On the statistical role of inexact matching in observational studies pp. 631-644

Kevin Guo and Dominik Rothenhäusler

Assessing time-varying causal effect moderation in the presence of cluster-level treatment effect heterogeneity and interference pp. 645-662

J Shi, Z Wu and W Dempsey

Honest calibration assessment for binary outcome predictions pp. 663-680

Timo Dimitriadis, Lutz Dümbgen, Alexander Henzi, Marius Puke and Johanna Ziegel

Thresholded graphical lasso adjusts for latent variables pp. 681-697

Minjie Wang and Genevera I Allen

Spectral adjustment for spatial confounding pp. 699-719

Yawen Guan, Garritt L Page, Brian J Reich, Massimo Ventrucci and Shu Yang

Dependent censoring based on parametric copulas pp. 721-738

C Czado and I Van Keilegom

Variable elimination, graph reduction and the efficient g-formula pp. 739-761

F Richard Guo, Emilija Perković and Andrea Rotnitzky

Existence of matching priors on compact spaces pp. 763-776

Haosui Duanmu, Daniel M Roy and Aaron Smith

High-dimensional analysis of variance in multivariate linear regression pp. 777-797

Zhipeng Lou, Xianyang Zhang and Wei Biao Wu

Testing Kronecker product covariance matrices for high-dimensional matrix-variate data pp. 799-814

Long Yu, Jiahui Xie and Wang Zhou

Marginal proportional hazards models for multivariate interval-censored data pp. 815-830

Yangjianchen Xu, Donglin Zeng and D Y Lin

Median regularity and honest inference pp. 831-838

Arun Kumar Kuchibhotla, Sivaraman Balakrishnan and Larry Wasserman

Volume 110, issue 2, 2023

On boosting the power of Chatterjee’s rank correlation pp. 283-299

Z Lin and F Han

Hug and hop: a discrete-time, nonreversible Markov chain Monte Carlo algorithm pp. 301-318

M Ludkin and C Sherlock

Gaussian universal likelihood ratio testing pp. 319-337

Robin Dunn, Aaditya Ramdas, Sivaraman Balakrishnan and Larry Wasserman

Gradient-based sparse principal component analysis with extensions to online learning pp. 339-360

Yixuan Qiu, Jing Lei and Kathryn Roeder

Additive models for symmetric positive-definite matrices and Lie groups pp. 361-379

Z Lin, H -G Müller and B U Park

Functional linear regression for discretely observed data: from ideal to reality pp. 381-393

Hang Zhou, Fang Yao and Huiming Zhang

Multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring pp. 395-410

Hunyong Cho, Shannon T Holloway, David J Couper and Michael R Kosorok

Kernel two-sample tests in high dimensions: interplay between moment discrepancy and dimension-and-sample orders pp. 411-430

Jian Yan and Xianyang Zhang

Lasso-adjusted treatment effect estimation under covariate-adaptive randomization pp. 431-447

Hanzhong Liu, Fuyi Tu and Wei Ma

Evaluating causes of effects by posterior effects of causes pp. 449-465

Zitong Lu, Zhi Geng, Wei Li, Shengyu Zhu and Jinzhu Jia

Design-based theory for cluster rerandomization pp. 467-483

Xin Lu, Tianle Liu, Hanzhong Liu and Peng Ding

Sample-constrained partial identification with application to selection bias pp. 485-498

Matthew J Tudball, Rachael A Hughes, Kate Tilling, Jack Bowden and Qingyuan Zhao

Bootstrapping Whittle estimators pp. 499-518

J -P Kreiss and E Paparoditis

A multiplicative structural nested mean model for zero-inflated outcomes pp. 519-536

Miao Yu, Wenbin Lu, Shu Yang and Pulak Ghosh

Optimal row-column designs pp. 537-549

Zheng Zhou and Yongdao Zhou

Clustering consistency with Dirichlet process mixtures pp. 551-558

F Ascolani, A Lijoi, Giovanni Rebaudo and G Zanella

Volume 110, issue 1, 2023

Propensity scores in the design of observational studies for causal effects pp. 1-13

P R Rosenbaum and D B Rubin

Subsampling sparse graphons under minimal assumptions pp. 15-32

Robert Lunde and Purnamrita Sarkar

Localized conformal prediction: a generalized inference framework for conformal prediction pp. 33-50

Leying Guan

Uniform inference in high-dimensional Gaussian graphical models pp. 51-68

S Klaassen, J Kueck, M Spindler and Victor Chernozhukov

On F-modelling-based empirical Bayes estimation of variances pp. 69-81

Yeil Kwon and Zhigen Zhao

Testing generalized linear models with high-dimensional nuisance parameters pp. 83-99

Jinsong Chen, Quefeng Li and Hua Yun Chen

Data integration: exploiting ratios of parameter estimates from a reduced external model pp. 119-134

Jeremy M G Taylor, Kyuseong Choi and Peisong Han

Spherical clustering in detection of groups of concomitant extremes pp. 135-153

V Fomichov and J Ivanovs

Minimax designs for causal effects in temporal experiments with treatment habituation pp. 155-168

Guillaume W Basse, Yi Ding and Panos Toulis

Robust differential abundance test in compositional data pp. 169-185

Shulei Wang

Linearized maximum rank correlation estimation pp. 187-203

Guohao Shen, Kani Chen, Jian Huang and Yuanyuan Lin

Response best-subset selector for multivariate regression with high-dimensional response variables pp. 205-223

Jianhua Hu, Jian Huang, Xiaoqian Liu and Xu Liu

Separable expansions for covariance estimation via the partial inner product pp. 225-247

T Masak, S Sarkar and V M Panaretos

Seeded binary segmentation: a general methodology for fast and optimal changepoint detection pp. 249-256

S Kovács, P Bühlmann, H Li and A Munk

A simple and general debiased machine learning theorem with finite-sample guarantees pp. 257-264

Victor Chernozhukov, W K Newey and R Singh

Regression of exchangeable relational arrays pp. 265-272

F W Marrs, B K Fosdick and T H Mccormick

Optimal minimax random designs for weighted least squares estimators pp. 273-280

D Azriel