Papers to Appear in Subsequent Issues

When papers are accepted for publication, they will appear below. Any changes that are made during the production process will only appear in the final version. Papers listed here are not updated during the production process and are removed once an issue is published.

Response-adaptive randomization in clinical trials: from myths to practical considerations David S Robertson, Kim May Lee, Boryana C Lopez-Kolkovska, and Sofia S Villar
Comment: A Quarter Century of Methodological Research in Response-Adaptive Randomization Anastasia Ivanova and William F Rosenberger
Discussion of “Response-adaptive randomization in clinical trials: from myths to practical considerations” Yunshan Duan, Peter Mueller, and Yuan Ji
Advancing Clinical Trials with Novel Designs and Implementations Lorenzo Trippa and Yanxun Xu
Group sequential designs with response-adaptive randomisation Christopher Jennison
Is Response-Adaptive Randomization a “good thing” or not in clinical trials? Why we cannot take sides Alessandra Giovagnoli
Response Adaptive Randomization in Practice: A Discussion of Robertson et al. Scott M Berry and Kert Viele
Rejoinder: Response-adaptive randomization in clinical trials David S. Robertson, Kim May Lee, Boryana C. López-Kolkovska, and Sofía S. Villar
Efficient data augmentation techniques for some classes of state space models Linda S. L. Tan
Distributed Bayesian Inference in Massive Spatial Data Rajarshi Guhaniyogi, Cheng Li, Terrance Savitsky, and Sanvesh Srivastava
The Secret Life of I. J. Good Sandy Zabell
Cross-study replicability in cluster analysis Lorenzo Masoero, Emma Thomas, Giovanni Parmigiani, Svitlana Tyekucheva, and Lorenzo Trippa
Principal Fairness for Human and Algorithmic Decision-Making Kosuke Imai and Zhichao Jiang
Conversations with Gábor J. Székely Yulia R. Gel, Judy Wang, and Edsel Pena
Confidence and discoveries with e-values Vladimir Vovk and Ruodu Wang
Approximating Bayes in the 21st Century Gael M Martin, David T Frazier, and Christian P Robert
Computing Bayes: From Then `Til Now Gael M Martin, David T Frazier, and Christian P Robert
A Conversation with Mary E. Thompson Rhonda J. Rosychuk
A Conversation with Stephen M. Stigler Sam Behseta
The role of exchangeability in causal inference Olli Saarela, David A. Stephens, and Erica E. M. Moodie
Aitchison’s Compositional Data Analysis 40 years On: A Reappraisal Michael Greenacre, Eric Grunsky, John Bacon-Shone, Ionas Erb, and Thomas Quinn
Statistical embedding: Beyond principal components Dag Tjøstheim, Martin Jullum, and Anders Løland
Are Biases That Matter Detectable in Observational Studies? Paul R Rosenbaum
Experimental Design in Marketplaces Patrick Bajari, Brian Burdick, Guido Imbens, Lorenzo Masoero, James Mcqueen, Thomas Richardson, and Ido Rosen
A probabilistic view on predictive constructions for Bayesian learning Patrizia Berti, Emanuela Dreassi, Fabrizio Leisen, Luca Pratelli, and Pietro Rigo
Parameter Restrictions for the Sake of Identification: Is there Utility in Asserting that Perhaps a Restriction Holds? Paul Gustafson
Variational inference for cutting feedback in misspecified models Xuejun Yu, David John Nott, and Michael Stanley Smith
Note on Legendre’s Method of Least Squares Jukka Nyblom
Living on the Edge: An Unified Approach to Antithetic Sampling Roberto Casarin, Radu V. Craiu, Lorenzo Frattarolo, and Christian P. Robert
Causal inference methods for combining randomized trials and observational studies: a review Bénédicte Colnet, Imke Mayer, Guanhua Chen, Awa Dieng, Ruohong Li, Gaël Varoquaux, Jean-Philippe Vert, Julie Josse, and Shu Yang
Methods for Integrating Trials and Non-Experimental Data to Examine Treatment Effect Heterogeneity Carly Lupton Brantner, Ting-Hsuan Chang, Trang Quynh Nguyen, Hwanhee Hong, Leon DiStefano, and Elizabeth A. Stuart
Defining Replicability of Prediction Rules Giovanni Parmigiani
Replicability Across Multiple Studies Marina Bogomolov and Ruth Heller