| 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
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| 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
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| Laplace’s theories of cognitive illusions, heuristics, and biases |
Andrew Gelman and Joshua Miller
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| Matching Methods for Observational Studies Derived from Large Administrative Databases |
Ruoqi Yu, Jeffrey H Silber, and Paul R Rosenbaum
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| Sparse regression: Scalable algorithms and empirical performance |
Dimitris Bertsimas, Jean Pauphilet, and Bart Van Parys
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| 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
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| Convex Relaxation Methods for Community Detection |
Xiaodong Li, Yudong Chen, and Jiaming Xu
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| Fano’s inequality for random variables |
Sebastien Gerchinovitz, Pierre Menard, and Gilles Stoltz
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| Larry Brown’s Contributions to Parametric Inference, Decision Theory and Foundations: A Survey |
James Berger and Anirban DasGupta
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| Gaussianization Machines for Non-Gaussian Function Estimation Models |
Tony Cai
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| Equitability, Interval Estimation, and Statistical Power |
Yakir Reshef, David Reshef, Pardis Sabeti, and Michael Mitzenmacher
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| Linear mixed models under endogeneity: modeling sequential treatment effects with application to a mobile health study |
Tianchen Qian, Predrag Klasnja, and Susan A. Murphy
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| Invariance, Causality and Robustness |
Peter Bühlmann
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| Discussion of Models as Approximations I & II |
Sara Anna van de Geer
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| Comment on Models as Approximations, Parts I and II, by Buja et al. |
Jerald Lawless
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| 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
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| Discussion of Buja et al Models as approximations I and II |
Dag Bjarne Tjostheim
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| 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
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| LGM split sampler: An efficient MCMC sampling scheme for latent Gaussian models |
Óli Páll Geirsson, Birgir Hrafnkelsson, Daniel Simpson, and Helgi Sigurdarson
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| Outcome-wide longitudinal designs for causal inference: a new template for empirical studies |
Tyler J VanderWeele, Maya B Mathur, and Ying Chen
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| Risk models for breast cancer and their validation |
Adam Robert Brentnall and Jack Cuzick
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| Some Statistical Issues in Climate Science |
Michael Stein
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| Checking for prior-data conflict using prior-to-posterior divergences |
David John Nott, Xueou Wang, Michael Evans, and Berthold-Georg Englert
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| A Generalized Approach to Power Analysis for Local Average Treatment Effects |
Kirk Bansak
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| Best Subset, Forward Stepwise, or Lasso? Analysis and Recommendations Based on Extensive Comparisons |
Trevor hastie, Robert Tibshirani, and Ryan Tibshirani
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| A Conversation with Grace Wahba |
Douglas Nychka, Ping Ma, and Douglas Bates
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| A nonparametric super-efficient estimator of the average treatment effect |
David Benkeser, Wilson Cai, and Mark J van der Laan
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| Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing |
Chao Gao and Zongming Ma
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| On the probability that two random integers are coprime |
Jing Lei and Joseph B. Kadane
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| A Tale of Two Parasites: statistical modelling to support disease control programmes in Africa |
Peter John Diggle, Emanuele Giorgi, Julienne Atsame, Sylvie Ntsama Ella, Kisito Ogoussan, and Katherine Gass
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| Computational considerations when matching in large samples |
Fredrik Sävje
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| Comment |
Mark M Fredrickson, Josh Errickson, and Ben B Hansen
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| Commentary on Yu et al.: Opportunities and Challenges for Matching Methods in Large Databases |
Elizabeth A Stuart and Benjamin Ackerman
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| Comparative Study of Differentially Private Data Synthesis Methods |
Claire McKay Bowen and Fang Liu
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| 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
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| (Some of) Larry Brown’s work on admissibility |
Iain M Johnstone
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| Quantum Science and Quantum Technology |
Yazhen Wang
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| Discussion of the papers by Buja et al. |
Anthony Davison, Erwan Koch, and Jonathan Koh
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| Models as (deliberate) approximations |
David Whitney, Ali Shojaie, and Marco Carone
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| Statistical Inference From a Predictive Perspective |
Alessandro Rinaldo, Ryan Tibshirani, and Larry Wasserman
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| Bipartite Causal Inference with Interference |
Corwin M Zigler and Georgia Papadogeorgou
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| Laplace and Cognitive Illusions |
Daniel Kahneman and Maya Bar-Hillel
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| Comment: Illusions, Then and Now |
Glenn Shafer
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| Statistical Methodology in Single-Molecule Experiments |
Chao Du and Samuel Kou
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| Statistical Molecule Counting in Super-Resolution Fluorescence Microscopy: Towards Quantitative Nanoscopy |
Thomas Staudt, Timo Aspelmeier, Oskar Laitenberger, Claudia Geisler, Alexander Egner, and Axel Munk
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| Statisticians’ Views on Data Science |
Junhui Cai, Avishai Mandelbaum, Chaitra Nagaraja, Haipeng Shen, and Linda Zhao
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| A general framework for Vecchia approximations of Gaussian processes |
Matthias Katzfuss and Joseph Guinness
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| Discussion of “Models as Approximations, Parts I & II” by Andreas Buja and coauthors |
Dalia Ghanem and Todd A. Kuffner
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| Additive and multiplicative effects network models |
Peter Hoff
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| A Unified Primal Dual Active Set Algorithm for Nonconvex Sparse Recovery |
Jian Huang, Yuling Jiao, Bangti Jin, Jin Liu, Xiliang Lu, and Can Yang
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| A statistical framework for modern network science |
Harry Crane and Walter Dempsey
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