OOIR: Observatory of International Research

Papers

(The median citation count of Statistical Science is 1. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-06-01 to 2025-06-01.)

Article	Citations
Emerging Directions in Bayesian Computation	66
Being a Public Health Statistician During a Global Pandemic	41
A Cheat Sheet for Bayesian Prediction	40
The Dependent Dirichlet Process and Related Models	35
Approximating Bayes in the 21st Century	31
A Regression Perspective on Generalized Distance Covariance and the Hilbert–Schmidt Independence Criterion	28
Methods for Integrating Trials and Non-experimental Data to Examine Treatment Effect Heterogeneity	27
30 Years of Synthetic Data	27
Diffusion Schrödinger Bridges for Bayesian Computation	26
Randomization-Based Test for Censored Outcomes: A New Look at the Logrank Test	25
No Need for an Oracle: The Nonparametric Maximum Likelihood Decision in the Compound Decision Problem Is Minimax	21
Protecting Classifiers from Attacks	19
A Horse Race between the Block Maxima Method and the Peak–over–Threshold Approach	18
In Defense of the Indefensible: A Very Naïve Approach to High-Dimensional Inference	18
Rejoinder: Response-Adaptive Randomization in Clinical Trials	17
Note on Legendre’s Method of Least Squares	17
Protocols for Observational Studies: Methods and Open Problems	16
Bayesian Dependent Mixture Models: A Predictive Comparison and Survey	15
Revisiting the Gelman–Rubin Diagnostic	14
Interpreting p-Values and Confidence Intervals Using Well-Calibrated Null Preference Priors	13
Distributionally Robust and Generalizable Inference	13
A Bayesian “Sandwich” for Variance Estimation	13
Comment: Group Sequential Designs with Response-Adaptive Randomisation	13
Aitchison’s Compositional Data Analysis 40 Years on: A Reappraisal	11
Diffusion Smoothing for Spatial Point Patterns	10

Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring	10
Bayesian Adaptive Randomization with Compound Utility Functions	10
Identification of Causal Effects Within Principal Strata Using Auxiliary Variables	10
Statistical Embedding: Beyond Principal Components	9
Editorial: Special Issue on Reproducibility and Replicability	9
Parameter Restrictions for the Sake of Identification: Is There Utility in Asserting That Perhaps a Restriction Holds?	9
Khinchin’s 1929 Paper on Von Mises’ Frequency Theory of Probability	9
A Problem in Forensic Science Highlighting the Differences between the Bayes Factor and Likelihood Ratio	8
Editorial: Bayesian Computations in the 21st Century	8
Cross-Study Replicability in Cluster Analysis	8
A Conversation with Mary E. Thompson	8
A Conversation with Guido W. Imbens	7
Bayesian Sample Size Determination for Causal Discovery	7
Sampling Algorithms in Statistical Physics: A Guide for Statistics and Machine Learning	7
A Conversation with Stephen Portnoy	7
Game-Theoretic Statistics and Safe Anytime-Valid Inference	6
Comment: Response Adaptive Randomization in Practice	6
Scalable Empirical Bayes Inference and Bayesian Sensitivity Analysis	6
On the Certainty of an Inductive Inference: The Binomial Case	5
Measurement Error Models: From Nonparametric Methods to Deep Neural Networks	5
Online Multiple Hypothesis Testing	5
Comments on Confidence as Likelihood by Pawitan and Lee in Statistical Science, November 2021	5
Choosing Among Notions of Multivariate Depth Statistics	5
Seven Principles for Rapid-Response Data Science: Lessons Learned from Covid-19 Forecasting	5
Data, Science, and Global Disasters	4
Antoine Gombaud, Chevalier de Méré	4
Preamble	4
Confidence as Likelihood	3
Power Calculations for Replication Studies	3
A Comparative Tour through the Simulation Algorithms for Max-Stable Processes	3
The van Trees Inequality in the Spirit of Hájek and Le Cam	3
The Secret Life of I. J. Good	3
Distributed Bayesian Inference in Massive Spatial Data	3
Statistical Modeling for Practical Pooled Testing During the COVID-19 Pandemic	3
Computing Bayes: From Then ‘Til Now	2
The Costs and Benefits of Uniformly Valid Causal Inference with High-Dimensional Nuisance Parameters	2
High-Performance Statistical Computing in the Computing Environments of the 2020s	2
Likelihood Asymptotics in Nonregular Settings: A Review with Emphasis on the Likelihood Ratio	2
Double-Estimation-Friendly Inference for High-Dimensional Misspecified Models	2
Principal Fairness for Human and Algorithmic Decision-Making	2
Comment: Response-Adaptive Randomization in Clinical Trials: From Myths to Practical Considerations	2
Maximum Likelihood Multiple Imputation: Faster Imputations and Consistent Standard Errors Without Posterior Draws	2
Comparison of Two Frameworks for Analyzing Longitudinal Data	2
Statistical Aspects of the Quantum Supremacy Demonstration	2
The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning	2
Bayesian Analysis of Rank Data with Covariates and Heterogeneous Rankers	2
Data Science in a Time of Crisis: Lessons from the Pandemic	2
In Praise (and Search) of J. V. Uspensky	1
Conversations with Gábor J. Székely	1
Comment: Protocols for Observational Studies: An Application to Regression Discontinuity Designs	1

Real-Time Estimation of COVID-19 Infections: Deconvolution and Sensor Fusion	1
Martingale Posterior Distributions for Time-Series Models	1
Statistical Frameworks for Oncology Dose-Finding Designs with Late-Onset Toxicities: A Review	1
The Role of Exchangeability in Causal Inference	1
A General Construction of Multivariate Dependence Structures with Nonmonotone Mappings and Its Applications	1
Replication Success Under Questionable Research Practices—a Simulation Study	1
J. B. S. Haldane’s Rule of Succession	1
Methods to Compute Prediction Intervals: A Review and New Results	1
Tracking Truth Through Measurement and the Spyglass of Statistics	1
Past, Present and Future of Software for Bayesian Inference	1
Interoperability of Statistical Models in Pandemic Preparedness: Principles and Reality	1
Advances in Projection Predictive Inference	1
Comment: Is Response-Adaptive Randomization a “Good Thing” or Not in Clinical Trials? Why We Cannot Take Sides	1
Experimental Design in Marketplaces	1
A Conversation with Ross Prentice	1
A Conversation with Don Dawson	1
Studentization Versus Variance Stabilization: A Simple Way Out of an Old Dilemma	1