Papers to Appear in Subsequent Issues

Models as Approximations, Part I: A Conspiracy of Random Regressors and Model Deviations Against Classical Inference in Regression Andreas Buja, Richard Berk, Lawrence Brown, Edward George, Emil Pitkin, Mikhail Traskin, Linda Zhao, and Kai Zhang
Models as Approximations — Part II: A General Theory of Model-Robust Regression Andreas Buja, Richard Berk, Lawrence Brown, Ed George, Arun Kumar Kuchibhotla, and Linda Zhao
Laplace’s theories of cognitive illusions, heuristics, and biases Andrew Gelman and Joshua Miller
ROS Regression: Integrating Regularization with Optimal Scaling Regression Jacqueline J Meulman, Anita J van der Kooij, and Kevin Duisters
An Overview of Semiparametric Extensions of Finite Mixture Models Sijia Xiang, Weixin Yao, and Guangren Yang
Matching Methods for Observational Studies Derived from Large Administrative Databases Ruoqi Yu, Jeffrey H Silber, and Paul R Rosenbaum
Lasso Meets Horseshoe : A Survey Anindya Bhadra, Jyotishka Datta, Nicholas G. Polson, and Brandon Willard
Sparse regression: Scalable algorithms and empirical performance Dimitris Bertsimas, Jean Pauphilet, and Bart Van Parys
The Geometry of Continuous Latent Space Models for Network Data Anna Lantz Smith, Dena M Asta, and Catherine A Calder
A Conversation with Peter Diggle Peter Atkinson and Jorge Mateu
User-Friendly Covariance Estimation for Heavy-Tailed Distributions Yuan Ke, Stanislav Minsker, Zhao Ren, Qiang Sun, and Wen-Xin Zhou
Conditionally conjugate mean-field variational Bayes for logistic models Daniele Durante and Tommaso Rigon
Assessing the causal effect of binary interventions from observational panel data with few treated units Pantelis Samartsidis, Shaun R Seaman, Anne M Presanis, Matthew Hickman, and Daniela De Angelis
Model-based approach to the joint analysis of single-cell data on chromatin accessibility and gene expression Zhixiang Lin, Mahdi Zamanighomi, Timothy Daley, Shining Ma, and Wing Hung Wong
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
Larry Brown’s Contributions to Parametric Inference, Decision Theory and Foundations: A Survey James Berger and Anirban DasGupta
Gaussianization Machines for Non-Gaussian Function Estimation Models Tony Cai
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
Discussion of Models as Approximations I & II Sara Anna van de Geer
Comment on Models as Approximations, Parts I and II, by Buja et al. Jerald Lawless
Comment on “Models as Approximations, Parts I and II” Nikki L. B. Freeman, Xiaotong Jiang, Owen E. Leete, Daniel J. Luckett, Teeranan (Ben) Pokaprakarn, and Michael R. Kosorok
Discussion of Buja et al Models as approximations I and II Dag Bjarne Tjostheim
Comment on “Models as Approximations 1: Consequences Illustrated with Linear Regression” by A. Buja, R. Berk, L. Brown, E. George, E. Pitkin, L. Zhan, and K. Zhang Roderick Joseph Little
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