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
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
Computing Bayes: Bayesian Computation from 1763 to 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
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