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 2022-05-01 to 2026-05-01.)

Article	Citations
A Regression Perspective on Generalized Distance Covariance and the Hilbert–Schmidt Independence Criterion	75
30 Years of Synthetic Data	73
Sample-Based Planning and Learning with Function Approximation	60
A Cheat Sheet for Bayesian Prediction	41
Emerging Directions in Bayesian Computation	40
Approximating Bayes in the 21st Century	30
Rejoinder: Item Response Theory—A Statistical Framework for Educational and Psychological Measurement	30
Being a Public Health Statistician During a Global Pandemic	29
No Need for an Oracle: The Nonparametric Maximum Likelihood Decision in the Compound Decision Problem Is Minimax	28
Methods for Integrating Trials and Non-experimental Data to Examine Treatment Effect Heterogeneity	25
Diffusion Schrödinger Bridges for Bayesian Computation	24
Randomization-Based Test for Censored Outcomes: A New Look at the Logrank Test	23
From Corrado Gini’s Early Contributions to Overdispersion to Modern Models of Voting Behaviour	23
Protecting Classifiers from Attacks	21
Cox Reduction and Confidence Sets of Models: A Theoretical Elucidation	19
Note on Legendre’s Method of Least Squares	17
Rejoinder: Response-Adaptive Randomization in Clinical Trials	16
Bayesian Dependent Mixture Models: A Predictive Comparison and Survey	15
Protocols for Observational Studies: Methods and Open Problems	15
Interpreting p-Values and Confidence Intervals Using Well-Calibrated Null Preference Priors	14
Meta Representation Learning with Contextual Linear Bandits	14
Comment: Group Sequential Designs with Response-Adaptive Randomisation	13
A Bayesian “Sandwich” for Variance Estimation	13
On the Mixed-Model Analysis of Covariance in Cluster-Randomized Trials	12
Distributionally Robust and Generalizable Inference	11

Item Response Theory—A Statistical Framework for Educational and Psychological Measurement	11
Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring	10
Bayesian Adaptive Randomization with Compound Utility Functions	10
Aitchison’s Compositional Data Analysis 40 Years on: A Reappraisal	10
On the Use of Auxiliary Variables in Multilevel Regression and Poststratification	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
Editorial: Bayesian Computations in the 21st Century	7
Multivariate Matérn Models—a Spectral Approach	7
Randomized and Exchangeable Improvements of Markov’s, Chebyshev’s and Chernoff’s Inequalities	7
Cross-Study Replicability in Cluster Analysis	7
A Conversation with Stephen Portnoy	7
A Conversation with Mary E. Thompson	7
A Conversation with Guido W. Imbens	7
Approximate Inference with Exponential Tilting Densities: Theory and Applications	6
Seven Principles for Rapid-Response Data Science: Lessons Learned from Covid-19 Forecasting	6
Online Multiple Hypothesis Testing	6
Bayesian Sample Size Determination for Causal Discovery	6
Comments on Confidence as Likelihood by Pawitan and Lee in Statistical Science, November 2021	6
Comment: Response Adaptive Randomization in Practice	6
Sampling Algorithms in Statistical Physics: A Guide for Statistics and Machine Learning	6
Game-Theoretic Statistics and Safe Anytime-Valid Inference	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
Choosing Among Notions of Multivariate Depth Statistics	5
Demystifying Inferential Models and Confidence Curves: A Fiducial Perspective	5
Survey on Algorithms for Multi-Index Models	5
Antoine Gombaud, Chevalier de Méré	4
Data, Science, and Global Disasters	4
The Secret Life of I. J. Good	4
The Central Role of the Loss Function in Reinforcement Learning	4
Preamble	4
Conditionality Principle Under Unconstrained Randomness	4
Statistical Modeling for Practical Pooled Testing During the COVID-19 Pandemic	4
Markov Chain Monte Carlo Significance Tests	4
Power Calculations for Replication Studies	4
Distributed Bayesian Inference in Massive Spatial Data	4
The van Trees Inequality in the Spirit of Hájek and Le Cam	4
Double-Estimation-Friendly Inference for High-Dimensional Misspecified Models	4
Editorial: Special Issue on “Learning Across Distribution Shifts”	3
The Costs and Benefits of Uniformly Valid Causal Inference with High-Dimensional Nuisance Parameters	3
Comment: Response-Adaptive Randomization in Clinical Trials: From Myths to Practical Considerations	3
Efficient Generalization and Transportation	3
On Matérn Covariance and Gaussian Markov Random Fields: A Spectral Analysis	3
Principal Fairness for Human and Algorithmic Decision-Making	3
Statistical Aspects of the Quantum Supremacy Demonstration	3
Review of Quasi-Randomization Approaches for Estimation from Nonprobability Samples	3
The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning	3

High-Performance Statistical Computing in the Computing Environments of the 2020s	2
Computing Bayes: From Then ‘Til Now	2
A Geometric Perspective on Bayesian and Generalized Fiducial Inference	2
The Theory of Online Control	2
Evidence Bounds in Singular Models: Probabilistic and Variational Perspectives	2
A Primer on Bayesian Neural Networks: Review and Debates	2
Past, Present and Future of Software for Bayesian Inference	2
Comment: The Evolution of Items and Responses in IRT	2
What You See Is Not What Is There: Mechanisms, Models and Methods for Point Pattern Deviations	2
Data Science in a Time of Crisis: Lessons from the Pandemic	2
A Note on Distance Variance for Categorical Variables	2
Comment: Is Response-Adaptive Randomization a “Good Thing” or Not in Clinical Trials? Why We Cannot Take Sides	1
In Praise (and Search) of J. V. Uspensky	1
Catalytic Priors: Using Synthetic Data to Specify Prior Distributions in Bayesian Analysis	1
Real-Time Estimation of COVID-19 Infections: Deconvolution and Sensor Fusion	1
Conversations with Gábor J. Székely	1
Statistical Frameworks for Oncology Dose-Finding Designs with Late-Onset Toxicities: A Review	1
A General Construction of Multivariate Dependence Structures with Nonmonotone Mappings and Its Applications	1
A Conversation with Stephen M. Stigler	1
Experimental Design in Marketplaces	1
Methods to Compute Prediction Intervals: A Review and New Results	1
Choosing Alpha Post Hoc: The Danger of Multiple Standard Significance Thresholds	1
Interoperability of Statistical Models in Pandemic Preparedness: Principles and Reality	1
Likelihood Asymptotics in Nonregular Settings: A Review with Emphasis on the Likelihood Ratio	1
Studentization Versus Variance Stabilization: A Simple Way Out of an Old Dilemma	1
Tracking Truth Through Measurement and the Spyglass of Statistics	1
Comment: Protocols for Observational Studies: An Application to Regression Discontinuity Designs	1
An Overview of Asymptotic Normality in Stochastic Blockmodels: Cluster Analysis and Inference	1
Re-Thinking Spatial Confounding in Spatial Linear Mixed Models	1
Replication Success Under Questionable Research Practices—a Simulation Study	1
Modern Statistical Models and Methods for Estimating Fatigue-Life and Fatigue-Strength Distributions from Experimental Data	1
J. B. S. Haldane’s Rule of Succession	1
The Role of Exchangeability in Causal Inference	1
Performative Prediction: Past and Future	1
Advances in Projection Predictive Inference	1
Gambler’s Ruin and the ICM	1
On the Statistical Complexity for Offline and Low-Adaptive Reinforcement Learning with Structures	1