Biometrika
Volume 89 - 112
Current editor(s): Paul Fearnhead From Biometrika Trust Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Bibliographic data for series maintained by Oxford University Press (). Access Statistics for this journal.
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Volume 112, issue 2, 2025
- Semiparametric local variable selection under misspecification pp. 192-225

- D Rossell, A K Seong, I Saez and M Guindani
- Assessing variable importance in survival analysis using machine learning pp. 333-43

- C J Wolock, P B Gilbert, N Simon and M Carone
- Bayesian clustering of high-dimensional data via latent repulsive mixtures pp. 551-8

- L Ghilotti, M Beraha and A Guglielmi
- Consistency of common spatial estimators under spatial confounding pp. 945-61

- Brian Gilbert, Elizabeth L Ogburn and Abhirup Datta
Volume 112, issue 1, 2025
- With random regressors, least squares inference is robust to correlated errors with unknown correlation structure pp. 1-35

- Zifeng Zhang, Peng Ding, Wen Zhou and Haonan Wang
- Multiple conditional randomization tests for lagged and spillover treatment effects pp. 3-16

- Yao Zhang and Qingyuan Zhao
- Studies in the history of probability and statistics, LI: the first conditional logistic regression pp. 89-100

- J A Hanley
- A robust covariate-balancing method for learning optimal individualized treatment regimes pp. 133-61

- Canhui Li, Donglin Zeng and Wensheng Zhu
- An adaptive null proportion estimator for false discovery rate control pp. 149-78

- Zijun Gao
- Estimating causal effects under non-individualistic treatments due to network entanglement pp. 235-67

- P Toulis, A Volfovsky and E M Airoldi
- Variance-based sensitivity analysis for weighting estimators results in more informative bounds pp. 235-40

- Melody Huang and Samuel D Pimentel
- The phase diagram of kernel interpolation in large dimensions pp. 242-52

- Haobo Zhang, Weihao Lu and Qian Lin
- Testing the mean and variance by e-processes pp. 289-300

- Yixuan Fan, Zhanyi Jiao and Ruodu Wang
- Axiomatization of interventional probability distributions pp. 507-56

- Kayvan Sadeghi and Terry Soo
- Semi-supervised distribution learning pp. 669-74

- Mengtao Wen, Yinxu Jia, Haojie Ren, Zhaojun Wang and Changliang Zou
- Boosting the power of kernel two-sample tests pp. 1148-59

- A Chatterjee and B B Bhattacharya
- Semiparametric efficiency gains from parametric restrictions on propensity scores pp. 1747-85

- Haruki Kono
- A note on e-values and multiple testing pp. 2055-85

- Guanxun Li and Xianyang Zhang
- Sensitivity models and bounds under sequential unmeasured confounding in longitudinal studies pp. 2645-57

- Zhiqiang Tan
- A simple bootstrap for Chatterjee’s rank correlation pp. 3070-102

- H Dette and M Kroll
- Causal inference with hidden mediators pp. 5633-751

- Amiremad Ghassami, Alan Yang, Ilya Shpitser and Eric Tchetgen Tchetgen
Volume 111, issue 4, 2024
- Optimal regimes for algorithm-assisted human decision-making pp. 1089-1108

- M J Stensrud, J D Laurendeau and A L Sarvet
- Exact selective inference with randomization pp. 1109-1127

- Snigdha Panigrahi, Kevin Fry and Jonathan Taylor
- Flexible control of the median of the false discovery proportion pp. 1129-1150

- Jesse Hemerik, Aldo Solari and Jelle J Goeman
- Radial neighbours for provably accurate scalable approximations of Gaussian processes pp. 1151-1167

- Yichen Zhu, Michele Peruzzi, Cheng Li and David B Dunson
- A rank-based sequential test of independence pp. 1169-1186

- Alexander Henzi and Michael Law
- Testing independence for sparse longitudinal data pp. 1187-1199

- Changbo Zhu, Junwen Yao and Jane-Ling Wang
- On some algorithms for estimation in Gaussian graphical models pp. 1201-1219

- S Højsgaard and S Lauritzen
- Network-adjusted covariates for community detection pp. 1221-1240

- Y Hu and W Wang
- Skip sampling: subsampling in the frequency domain pp. 1241-1256

- Tucker McElroy and Dimitris N Politis
- Individualized dynamic latent factor model for multi-resolutional data with application to mobile health pp. 1257-1275

- J Zhang, F Xue, Q Xu, J Lee and A Qu
- Difference-based covariance matrix estimation in time series nonparametric regression with application to specification tests pp. 1277-1292

- Lujia Bai and Weichi Wu
- Testing serial dependence or cross dependence for time series with underreporting pp. 1293-1312

- Keyao Wei, Lengyang Wang and Yingcun Xia
- Debiasing Welch’s method for spectral density estimation pp. 1313-1329

- Lachlan C Astfalck, Adam M Sykulski and Edward J Cripps
- Bootstrap test procedure for variance components in nonlinear mixed effects models in the presence of nuisance parameters and a singular Fisher information matrix pp. 1331-1348

- T Guédon, C Baey and E Kuhn
- Sensitivity analysis for matched observational studies with continuous exposures and binary outcomes pp. 1349-1368

- Jeffrey Zhang, Dylan S Small and Siyu Heng
- A model-free variable screening method for optimal treatment regimes with high-dimensional survival data pp. 1369-1386

- Cheng-Han Yang and Yu-Jen Cheng
- Inference for possibly misspecified generalized linear models with nonpolynomial-dimensional nuisance parameters pp. 1387-1404

- Shaoxin Hong, Jiancheng Jiang, Xuejun Jiang and Haofeng Wang
- More power by using fewer permutations pp. 1405-1412

- Nick W Koning
- Covariate adjustment in randomized experiments with missing outcomes and covariates pp. 1413-1420

- Anqi Zhao, Peng Ding and Fan Li
- On propensity score matching with a diverging number of matches pp. 1421-1428

- Yihui He and Fang Han
- Sharp symbolic nonparametric bounds for measures of benefit in observational and imperfect randomized studies with ordinal outcomes pp. 1429-1436

- Erin E Gabriel, Michael C Sachs and Andreas Kryger Jensen
- Inference for partial correlations of a multivariate Gaussian time series pp. 1437-1444

- A S Dilernia, M Fiecas and L Zhang
Volume 111, issue 3, 2024
- Selective conformal inference with false coverage-statement rate control pp. 727-742

- Yajie Bao, Yuyang Huo, Haojie Ren and Changliang Zou
- Central limit theorems for local network statistics pp. 743-754

- P A Maugis
- Generalized kernel two-sample tests pp. 755-770

- Hoseung Song and Hao Chen
- Graphical tools for selecting conditional instrumental sets pp. 771-788

- L Henckel, M Buttenschoen and M H Maathuis
- Doubly robust estimation under covariate-induced dependent left truncation pp. 789-808

- Yuyao Wang, Andrew Ying and Ronghui Xu
- Explicit solutions for the asymptotically optimal bandwidth in cross-validation pp. 809-823

- Karim M Abadir and Michel Lubrano
- Asymptotically constant risk estimator of the time-average variance constant pp. 825-842

- K W Chan and C Y Yau
- Efficient nonparametric estimation of Toeplitz covariance matrices pp. 843-864

- K Klockmann and T Krivobokova
- On the optimality of score-driven models pp. 865-880

- P Gorgi, C S A Lauria and A Luati
- Phylogenetic association analysis with conditional rank correlation pp. 881-902

- Shulei Wang, Bo Yuan, T Tony Cai and Hongzhe Li
- Network community detection using higher-order structures pp. 903-923

- X Yu and J Zhu
- Testing serial independence of object-valued time series pp. 925-944

- Feiyu Jiang, Hanjia Gao and Xiaofeng Shao
- Nonparametric priors with full-range borrowing of information pp. 945-969

- F Ascolani, B Franzolini, A Lijoi and I Prünster
- Maximum likelihood estimation for semiparametric regression models with interval-censored multistate data pp. 971-988

- Yu Gu, Donglin Zeng, Gerardo Heiss and D Y Lin
- On inference in high-dimensional logistic regression models with separated data pp. 989-1011

- R M Lewis and H S Battey
- Projective independence tests in high dimensions: the curses and the cures pp. 1013-1027

- Yaowu Zhang and Liping Zhu
- Familial inference: tests for hypotheses on a family of centres pp. 1029-1045

- Ryan Thompson, Catherine S Forbes, Steven N MacEachern and Mario Peruggia
- Regression analysis of group-tested current status data pp. 1047-1061

- Shuwei Li, Tao Hu, Lianming Wang, Christopher S McMahan and Joshua M Tebbs
- On the failure of the bootstrap for Chatterjee’s rank correlation pp. 1063-1070

- Zhexiao Lin and Fang Han
- A note on minimax robustness of designs against correlated or heteroscedastic responses pp. 1071-1075

- D P Wiens
- Second term improvement to generalized linear mixed model asymptotics pp. 1077-1084

- Luca Maestrini, Aishwarya Bhaskaran and Matt P Wand
Volume 111, issue 2, 2024
- The state of cumulative sum sequential changepoint testing 70 years after Page pp. 367-391

- Alexander Aue and Claudia Kirch
- On selection and conditioning in multiple testing and selective inference pp. 393-416

- Jelle J Goeman and Aldo Solari
- E-values as unnormalized weights in multiple testing pp. 417-439

- Nikolaos Ignatiadis, Ruodu Wang and Aaditya Ramdas
- More efficient exact group invariance testing: using a representative subgroup pp. 441-458

- N W Koning and J Hemerik
- Conformalized survival analysis with adaptive cut-offs pp. 459-477

- Yu Gui, Rohan Hore, Zhimei Ren and Rina Foygel Barber
- τ-censored weighted Benjamini–Hochberg procedures under independence pp. 479-496

- Haibing Zhao and Huijuan Zhou
- Kernel methods for causal functions: dose, heterogeneous and incremental response curves pp. 497-516

- R Singh, L Xu and A Gretton
- Selective machine learning of doubly robust functionals pp. 517-535

- Y Cui and E J Tchetgen Tchetgen
- Promises of parallel outcomes pp. 537-550

- Ying Zhou, Dingke Tang, Dehan Kong and Linbo Wang
- Order-based structure learning without score equivalence pp. 551-572

- Hyunwoong Chang, James J Cai and Quan Zhou
- Retrospective causal inference with multiple effect variables pp. 573-589

- Wei Li, Zitong Lu, Jinzhu Jia, Min Xie and Zhi Geng
- Likelihood-based inference under nonconvex boundary constraints pp. 591-607

- J Y Wang, Z S Ye and Y Chen
- On varimax asymptotics in network models and spectral methods for dimensionality reduction pp. 609-623

- J Cape
- A cross-validation-based statistical theory for point processes pp. 625-641

- Ottmar Cronie, Mehdi Moradi and Christophe A N Biscio
- Estimation of prediction error in time series pp. 643-660

- Alexander Aue and Prabir Burman
- An eigenvector-assisted estimation framework for signal-plus-noise matrix models pp. 661-676

- Fangzheng Xie and Dingbo Wu
- An anomaly arising in the analysis of processes with more than one source of variability pp. 677-689

- H S Battey and Peter McCullagh
- Covariate-adjusted log-rank test: guaranteed efficiency gain and universal applicability pp. 691-705

- Ting Ye, Jun Shao and Yanyao Yi
- Deep Kronecker network pp. 707-714

- Long Feng and Guang Yang
- Kernel interpolation generalizes poorly pp. 715-722

- Yicheng Li, Haobo Zhang and Qian Lin
Volume 111, issue 1, 2024
- Causal inference with misspecified exposure mappings: separating definitions and assumptions pp. 1-15

- F Sävje
- Discussion of ‘Causal inference with misspecified exposure mappings: separating definitions and assumptions’ pp. 17-20

- Michael Leung
- Discussion of ‘Causal inference with misspecified exposure mappings: separating definitions and assumptions’ pp. 21-24

- Eric Auerbach, Jonathan Auerbach and Max Tabord-Meehan
- Rejoinder: Causal inference with misspecified exposure mappings: separating definitions and assumptions pp. 25-29

- F Sävje
- A linear adjustment-based approach to posterior drift in transfer learning pp. 31-50

- Subha Maity, Diptavo Dutta, Jonathan Terhorst, Yuekai Sun and Moulinath Banerjee
- Efficient evaluation of natural stochastic policies in off-line reinforcement learning pp. 51-69

- Nathan Kallus and Masatoshi Uehara
- Universal robust regression via maximum mean discrepancy pp. 71-92

- P Alquier and M Gerber
- Online inference with debiased stochastic gradient descent pp. 93-108

- Ruijian Han, Lan Luo, Yuanyuan Lin and Jian Huang
- Hybrid confidence intervals for informative uniform asymptotic inference after model selection pp. 109-127

- Adam McCloskey
- One-step targeted maximum likelihood estimation for targeting cause-specific absolute risks and survival curves pp. 129-145

- H C W Rytgaard and M J van der Laan
- Populations of unlabelled networks: graph space geometry and generalized geodesic principal components pp. 147-170

- Anna Calissano, Aasa Feragen and Simone Vantini
- Statistical summaries of unlabelled evolutionary trees pp. 171-193

- Rajanala Samyak and Julia A Palacios
- Bayesian learning of network structures from interventional experimental data pp. 195-214

- F Castelletti and S Peluso
- Tailored inference for finite populations: conditional validity and transfer across distributions pp. 215-233

- Ying Jin and Dominik Rothenhäusler
- Treatment effect quantiles in stratified randomized experiments and matched observational studies pp. 235-254

- Yongchang Su and Xinran Li
- A mark-specific quantile regression model pp. 255-272

- Lianqiang Qu, Liuquan Sun and Yanqing Sun
- On geometric convergence for the Metropolis-adjusted Langevin algorithm under simple conditions pp. 273-289

- Alain Oliviero-Durmus and Éric Moulines
- Interpolating discriminant functions in high-dimensional Gaussian latent mixtures pp. 291-308

- Xin Bing and Marten Wegkamp
- Robust sample weighting to facilitate individualized treatment rule learning for a target population pp. 309-329

- Rui Chen, Jared D Huling, Guanhua Chen and Menggang Yu
- No-harm calibration for generalized Oaxaca–Blinder estimators pp. 331-338

- P L Cohen and C B Fogarty
- Characterizing M-estimators pp. 339-346

- Timo Dimitriadis Alfred Weber, Tobias FisslerRiskLab and Johanna Ziegel
- Scalable subsampling: computation, aggregation and inference pp. 347-354

- Dimitris N Politis
- Power and sample size calculations for rerandomization pp. 355-363

- Zach Branson, Inran Li and Peng Ding
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