Papers to Appear in Subsequent Issues

Laplace’s theories of cognitive illusions, heuristics, and biases Andrew Gelman and Joshua Miller
Matching Methods for Observational Studies Derived from Large Administrative Databases Ruoqi Yu, Jeffrey H Silber, and Paul R Rosenbaum
Sparse regression: Scalable algorithms and empirical performance Dimitris Bertsimas, Jean Pauphilet, and Bart Van Parys
Convex Relaxation Methods for Community Detection Xiaodong Li, Yudong Chen, and Jiaming Xu
Fano’s inequality for random variables Sebastien Gerchinovitz, Pierre Menard, and Gilles Stoltz
Equitability, Interval Estimation, and Statistical Power Yakir Reshef, David Reshef, Pardis Sabeti, and Michael Mitzenmacher
Linear mixed models under endogeneity: modeling sequential treatment effects with application to a mobile health study Tianchen Qian, Predrag Klasnja, and Susan A. Murphy
Invariance, Causality and Robustness Peter Bühlmann
LGM split sampler: An efficient MCMC sampling scheme for latent Gaussian models Óli Páll Geirsson, Birgir Hrafnkelsson, Daniel Simpson, and Helgi Sigurdarson
Outcome-wide longitudinal designs for causal inference: a new template for empirical studies Tyler J VanderWeele, Maya B Mathur, and Ying Chen
Checking for prior-data conflict using prior-to-posterior divergences David John Nott, Xueou Wang, Michael Evans, and Berthold-Georg Englert
A Generalized Approach to Power Analysis for Local Average Treatment Effects Kirk Bansak
Best Subset, Forward Stepwise, or Lasso? Analysis and Recommendations Based on Extensive Comparisons Trevor hastie, Robert Tibshirani, and Ryan Tibshirani
A Conversation with Grace Wahba Douglas Nychka, Ping Ma, and Douglas Bates
A nonparametric super-efficient estimator of the average treatment effect David Benkeser, Wilson Cai, and Mark J van der Laan
Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing Chao Gao and Zongming Ma
On the probability that two random integers are coprime Jing Lei and Joseph B. Kadane
Computational considerations when matching in large samples Fredrik Sävje
Comment Mark M Fredrickson, Josh Errickson, and Ben B Hansen
Commentary on Yu et al.:  Opportunities and Challenges for Matching Methods in Large Databases Elizabeth A Stuart and Benjamin Ackerman
Comparative Study of Differentially Private Data Synthesis Methods Claire McKay Bowen and Fang Liu
Exponential-Family Models of Random Graphs: Inference in Finite-, Super-, and Infinite-Population Scenarios Michael Schweinberger, Pavel N. Krivitsky, Carter T. Butts, and Jonathan Stewart
Bipartite Causal Inference with Interference Corwin M Zigler and Georgia Papadogeorgou
Laplace and Cognitive Illusions Daniel Kahneman and Maya Bar-Hillel
Comment:  Illusions, Then and Now Glenn Shafer
A general framework for Vecchia approximations of Gaussian processes Matthias Katzfuss and Joseph Guinness
Additive and multiplicative effects network models Peter Hoff
A Unified Primal Dual Active Set Algorithm for Nonconvex Sparse Recovery Jian Huang, Yuling Jiao, Bangti Jin, Jin Liu, Xiliang Lu, and Can Yang
A statistical framework for modern network science Harry Crane and Walter Dempsey
A Conversation with Francisco J. Samaniego George Gregory Roussas and Debasis Bhattacharya
Judicious Judgment Meets Unsettling Updating: Dilation, Sure Loss, and Simpson’s Paradox Ruobin Gong and Xiao-Li Meng
A Conversation with J. Stuart (Stu) Hunter Richard D. De Veaux
On general notions of depth for regression Yijun Zuo
Comment on: Invariance, Causality and Robustness by P.Buhlmann Vanessa Didelez
Discussion of ‘Outcome-wide longitudinal designs for causal inference’ Stijn Vansteelandt
Comment on “A nonparametric super-efficient estimator of the average treatment effect” by Benkeser, Cai, and van der Laan Mireille E Schnitzer
Outcome-wide individualized treatment strategies Ashkan Ertefaie and Brent A Johnson
Invariance and Causal Inference: Comment on a Paper by Buhlmann Stefan Wager
Automated analyses: Because we can, does it mean we should? Susan M Shortreed and Erica E.M. Moodie
Comment: A nonparametric super-efficient estimator of the average treatment effect Fan Li
A Conversation with Tze Leung Lai Zhiliang Ying, Dylan S. Small, and Ying Lu
A new template for empirical studies: from positivity to Positivity Rhian Mair Daniel
Clarifying endogeneous data structures and consequent modelling choices using causal graphs Erica E M Moodie and David A Stephens
The Box-Cox Transformation: Review and Extensions Anthony C Atkinson, Marco Riani, and Aldo Corbellini
Rejoinder to discussion of Laplace’s theories of cognitive illusions, heuristics, and biases Joshua Miller and Andrew Gelman
Non-commutative Probability and Multiplicative Cascades Ian Wray McKeague
Discussion of “Linear mixed models with endogenous covariates: modeling sequential treatment effects with application to a mobile health study” Kristin A Linn
Comment Hunyong Cho, Joshua Paul Zitovsky, Xinyi Li, Minxin Lu, Kushal Shah, John Sperger, Matthew C. B. Tsilimigras, and Michael Rene Kosorok
A selective overview of deep learning Jianqing Fan, Cong Ma, and Yiqiao Zhong
Stochastic Approximation: from Statistical Origin to Big-Data, Multidisciplinary Applications Tze Leung Lai and Hongsong Yuan
Robust high dimensional factor models with applications to statistical machine learning Jianqing Fan, Kaizheng Wang, Yiqiao Zhong, and Ziwei Zhu
On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning Lin Liu, Rajarshi Mukherjee, and James Matthew Robins