Journal of the American Statistical Association

Article	Citations
Classified Mixed Model Projections	347
Totally Concave Regression	76
Correction to “Modeling Time-Varying Random Objects and Dynamic Networks”	58
A Latent Variable Approach to Learning High-Dimensional Multivariate Longitudinal Data	49
Network Regression and Supervised Centrality Estimation	48
Consistent Least Squares Estimation in Population-Size-Dependent Branching Processes	43
U-Statistic Reduction: Higher-Order Accurate Risk Control and Statistical-Computational Trade-Off	43
Analysis of Variance of Tensor Product Reproducing Kernel Hilbert Spaces on Metric Spaces	42
Handbook of Bayesian, Fiducial, and Frequentist Inference	38
Sequential Knockoffs for Variable Selection in Reinforcement Learning	38
A Semiparametric Inverse Reinforcement Learning Approach to Characterize Decision Making for Mental Disorders	37
A Minimax Two-Sample Test for Functional Data via Grothendieck’s Divergence	35
Inside-Out Cross-Covariance for Spatial Multivariate Data	31
Censored Interquantile Regression Model with Time-Dependent Covariates	31
The Effect of Alcohol Intake on Brain White Matter Microstructural Integrity: A New Causal Inference Framework for Incomplete Phenomic Data	31
Exploration, Confirmation, and Replication in the Same Observational Study: A Two Team Cross-Screening Approach to Studying the Effect of Unwanted Pregnancy on Mothers’ Later Life Outcomes	30
In Nonparametric and High-Dimensional Models, Bayesian Ignorability is an Informative Prior	29
Scalable and Robust Regression Models for Continuous Proportional Data	29
Successive Classification Learning for Estimating Quantile Optimal Treatment Regimes	27
Subspace Estimation with Automatic Dimension and Variable Selection in Sufficient Dimension Reduction	26
Frequency-Band Estimation of the Number of Factors	25
Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process	24
Bayesian Conditional Transformation Models	24
Modern Applied Regressions: Bayesian and Frequentist Analysis of Categorical and Limited Response variables with R and StanModern Applied Regressions: Bayesian and Frequentist Analysis of Categorical	24
Kernel Estimation of Bivariate Time-Varying Coefficient Model for Longitudinal Data with Terminal Event	24

Rejoinder: A Scale-free Approach for False Discovery Rate Control in Generalized Linear Models	23
Rejoinder: LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures	23
A Random Projection Approach to Hypothesis Tests in High-Dimensional Single-Index Models	23
Fairness in Machine Learning: A Review for Statisticians	22
Theory of Statistical Inference	22
The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review	22
Comments on “Data Fission: Splitting a Single Data Point”	21
Translating Predictive Distributions into Informative Priors	21
Inferring Causal Effect of a Digital Communication Strategy under a Latent Sequential Ignorability Assumption and Treatment Noncompliance	20
Node-Level Community Detection within Edge Exchangeable Models for Interaction Processes	20
Reversible Jump PDMP Samplers for Variable Selection	20
Soccer Analytics: An Introduction Using R	20
Posterior Predictive Design for Phase I Clinical Trials	19
SPARCC: Semi-Parametric Robust Estimation in a Right-Censored Covariate Model	18
Discussion of “LAMBDA: Large Model Based Data Agent”	18
Conformal Prediction After Data-Dependent Model Selection	18
Optimal Dynamic Treatment Regimes and Partial Welfare Ordering	18
A Factor-Copula Latent-Vine Time Series Model for Extreme Flood Insurance Losses	18
Enveloped Huber Regression	18
Localized Sparse Principal Component Analysis of Multivariate Time Series in the Frequency Domain	18
Distributional Outcome Regression via Quantile Functions and its Application to Modelling Continuously Monitored Heart Rate and Physical Activity	18
Estimation and Variable Selection for Interval-Censored Failure Time Data with Random Change Point and Application to Breast Cancer Study	18
Double/Debiased Machine Learning for Treatment Effects in Dynamic Panels	17
Inference in High-Dimensional Multivariate Response Regression with Hidden Variables	17
Sparse Bayesian Multidimensional Item Response Theory	17
Matching on Generalized Propensity Scores with Continuous Exposures	17
Covariate-Informed Latent Interaction Models: Addressing Geographic & Taxonomic Bias in Predicting Bird–Plant Interactions	17
Two-Way Truncated Linear Regression Models with Extremely Thresholding Penalization	16
Collective Outlier Detection and Enumeration with Conformalized Closed Testing	16
Statistical Analytics for Health Data Science with SAS and R	16
CARE: Large Precision Matrix Estimation for Compositional Data	15
eDNAPlus: A Unifying Modeling Framework for DNA-based Biodiversity Monitoring	15
Weighted Functional Data Analysis for the Calibration of a Ground Motion Model in Italy	15
A Unified Inference for Predictive Quantile Regression	14
Statistical Prediction and Machine Learning	14
A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses with Evaluations on Administrative and Survey Data	14
Dynamic Decision Making With Individualized Variable Selection	14
On the Comparative Analysis of Average Treatment Effects Estimation via Data Combination	14
Model-Based Machine Learning	14
Low-Rank Online Dynamic Assortment with Dual Contextual Information	14
Bayesian Landmark-Based Shape Analysis of Tumor Pathology Images	13
Kernel Meets Sieve: Transformed Hazards Models with Sparse Longitudinal Covariates	13
Inference on the Proportion of Variance Explained in Principal Component Analysis	13
Factorial Difference-in-Differences	13
Bayesian Nonparametric Quasi Likelihood	13
Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning	13
Causality-Oriented Robustness: Exploiting General Noise Interventions	13
Structured Conformal Inference for Matrix Completion with Applications to Group Recommender Systems	13
Network Varying Coefficient Model	13
Improved Bounds and Inference on Optimal Regimes	13

Understanding Inequalities in Cancer Survival Using Bayesian Machine Learning	13
Optimal Differentially Private Ranking from Pairwise Comparisons	12
Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacy	12
Hypotheses Testing from Complex Survey Data Using Bootstrap Weights: A Unified Approach	12
Introduction to Quantitative Social Science with Python	12
Graphical Principal Component Analysis of Multivariate Functional Time Series	12
Conformal Prediction for Network-Assisted Regression	12
On Semiparametrically Dynamic Functional-Coefficient Autoregressive Spatio-Temporal Models with Irregular Location Wide Nonstationarity	12
Minimum Resource Threshold Policy Under Partial Interference	12
Robust Leave-One-Out Cross-Validation for High-Dimensional Bayesian Models	12
Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values	12
Financial Data Analytics with R: Monte-Carlo Validation	12
Discussion of “LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures”	12
Bayesian Transfer Learning for Enhanced Estimation and Inference	11
Doubly Flexible Estimation under Label Shift	11
Large-Scale Low-Rank Gaussian Process Prediction with Support Points	11
Parallelly Tempered Generative Adversarial Nets: Toward Stabilized Gradients	11
Asymptotic Distribution-Free Independence Test for High-Dimension Data	11
Differentially Private Permutation Tests	11
Double Generalized Linear Models: Likelihood and Bayesian Methods	11
Estimating Heterogeneous Exposure Effects in the Case-Crossover Design Using BART	11
Hyperbolic Network Latent Space Model with Learnable Curvature	11
Joint Spectral Clustering in Multilayer Degree-Corrected Stochastic Blockmodels	11
Group Network Hawkes Process	11
Robust Microbial Signature Discovery via Post-Selection Inference for Microbiome Compositions	11
On a Class of Sobolev Tests for Symmetry, their Detection Thresholds, and Asymptotic Powers	11
Identifiability and Inference for Generalized Latent Factor Models	11
Assessing the Most Vulnerable Subgroup to Type II Diabetes Associated with Statin Usage: Evidence from Electronic Health Record Data	11
Estimating the Spectral Density at Frequencies Near Zero	10
A Discussion on: “Data Fission: Splitting a Single Data Point” by Leiner, J., Duan, B., Wasserman, L. and Ramdas, A.	10
Data Fusion Using Weakly Aligned Sources	10
Scalable Bayesian Image-on-Scalar Regression for Population-Scale Neuroimaging Data Analysis	10
Higher-Order Accurate Two-Sample Network Inference and Network Hashing	10
Random Effects Model-Based Sufficient Dimension Reduction for Independent Clustered Data	10
An Efficient Monte Carlo Method for Valid Prior-Free Possibilistic Statistical Inference	10
Probability Modeling and Statistical Inference in Cancer Screening	10
Rate-Optimal Rank Aggregation with Private Pairwise Rankings	10
Individualized Dynamic Mediation Analysis Using Latent Factor Models	10
Optimal Run Order for Order-of-Addition Experiments	10
Discussion of “Data Fission: Splitting a Single Data Point” – Some Asymptotic Results for Data Fission	10
Graph-Aligned Random Partition Model (GARP)	10
Deep Regression for Repeated Measurements	10
Spatial Variation on Multiple Scales in Line Transect Data; the Case of Antarctic Fin Whales	10
Efficient Multimodal Sampling via Tempered Distribution Flow	10
Off-Policy Evaluation in Doubly Inhomogeneous Environments	9
Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process	9
Network Inference Using the Hub Model and Variants	9
Statistical Modeling with R: A Dual Frequentist and Bayesian Approach for Life Scientists	9
Causal Inference for Genomic Data with Multiple Heterogeneous Outcomes	9
Stationarity of Manifold Time Series	9
Modelling Spatial Density: Data, Methods, and R Applications in Statistics, Econometrics, and Machine Learning (by Katarzyna Kopczewska)	9
Spatial Statistics for Data Science: Theory and Practice with R.,	9
Natural Gradient Variational Bayes Without Fisher Matrix Analytic Calculation and Its Inversion	9
Power and Multicollinearity in Small Networks: A Discussion of “Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks” by Krivitsky, Coletti, and Hens	9
Bias Control for M-Quantile-Based Small Area Estimators	9
Estimation and Inference of Extremal Quantile Treatment Effects for Heavy-Tailed Distributions	9
Causal Inference for Social Network Data	9
Chain-Linked Multiple Matrix Integration via Embedding Alignment	9
Scaled Process Priors for Bayesian Nonparametric Estimation of the Unseen Genetic Variation	9
Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information	9
Learning When the Concept Shifts: Confounding, Invariance, and Dimension Reduction	9
Policy Learning with Distributional Welfare	9
Crowdsourcing Utilizing Subgroup Structure of Latent Factor Modeling	9
Theory for Identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework	9
Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Controls in Clinical Trials	9
A Decorrelating and Debiasing Approach to Simultaneous Inference for High-Dimensional Confounded Models	8
Robustifying Likelihoods by Optimistically Re-weighting Data	8
A Statistician’s Overview of Physics-Informed Neural Networks for Spatio-Temporal Data	8
An Additive Graphical Model for Discrete Data	8
Discussion of “A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks” by Pavel N. Krivitsky, Pietro Coletti, and Niel Hens	8
Generalized Linear Mixed Models: Modern Concepts, Methods and Applications, 2nd ed.	8
Scalable Estimation of Multinomial Response Models with Random Consideration Sets	8
Discussion of “LAMBDA: A Large Model Based Data Agent”	8
Belted and Ensembled Neural Network for Linear and Nonlinear Sufficient Dimension Reduction	8
Exact Decoding of a Sequentially Markov Coalescent Model in Genetics	8
Estimation and Inference of Quantile Spatially Varying Coefficient Models Over Complicated Domains	8
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm	8
Posterior Risk of Modular and Semi-Modular Bayesian Inference	8
Online Policy Learning and Inference by Matrix Completion	8
Testing Mutually Exclusive Hypotheses for Multi-Response Regressions	8

Confidently Comparing Estimates with the c-value	8
Causal Inference with Generative Artificial Intelligence: Application to Texts as Treatments	8
Nonparametric Multiple-Output Center-Outward Quantile Regression	7
Quantification of Vaccine Waning as a Challenge Effect	7
Recommender Systems: A Review	7
Cluster Quilting: Spectral Clustering for Patchwork Learning	7
Contextual Dynamic Pricing: Algorithms, Optimality, and Local Differential Privacy Constraints	7
A Novel Approach of High Dimensional Linear Hypothesis Testing Problem	7
Covariate-Adjusted Response-Adaptive Design with Delayed Outcomes	7
When Frictions Are Fractional: Rough Noise in High-Frequency Data	7
Toward Interpretable Deep Generative Models via Causal Representation Learning	7
Factor Augmented Inverse Regression and its Application to Microbiome Data Analysis	7
On a Notion of Graph Centrality Based on L 1 Data Depth	7
Deep Fréchet Regression	7
ℓ 1 -based Bayesian Ideal Point Model for Multidimensional Politics	7
On the Poor Statistical Properties of the P -Curve Meta-Analytic Procedure	7
Tail Risk in the Tail: Estimating High Quantiles When a Related Variable is Extreme	7
Learning with the Minimum Description Length Principle	7
Optimally adaptive test for high dimensional hypotheses via minimax deficiency	7
Unified Unconditional Regression for Multivariate Quantiles, M-Quantiles, and Expectiles	7
Gaussian Invariant Markov Chain Monte Carlo	7
Bayesian Signal Matching for Transfer Learning in ERP-Based Brain Computer Interface	7
Structural Equation Modeling Using R/SAS: A Step-by-Step Approach with Real Data Analysis	7
Systemic and Systematic Risks-Driven Marginal Expected Side-effect	7
Capture-Recapture Models with Heterogeneous Temporary Emigration	7
Ranking Inferences Based on the Top Choice of Multiway Comparisons	7
Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional Regression	7
Statistical Inference for Hüsler–Reiss Graphical Models Through Matrix Completions	6
Spatial Scale-Aware Tail Dependence Modeling for High-Dimensional Spatial Extremes	6
Inference for Dispersion and Curvature of Random Objects	6
Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors	6
Fast Approximation of the Shapley Values Based on Order-of-Addition Experimental Designs	6
Development of Public Health Policy by Digital Twin Microsimulation and Q-learning: A COVID-19 Booster Case Study	6
Blessing from Human-AI Interaction: Super Policy Learning in Confounded Environments	6
Clustering Social Media Users Using Categorical-Valued Functional Data Analysis	6
Manipulating an Instrumental Variable in an Observational Study of Premature Babies: Design, Bounds, and Inference	6
Robust Regression with Covariate Filtering: Heavy Tails and Adversarial Contamination	6
A Wasserstein Index of Dependence for Random Measures	6
Handbook of Matching and Weighting Adjustments for Causal Inference	6
An Efficient Coalescent Model for Heterochronously Sampled Molecular Data	6
Discovery and Inference of a Causal Network with Hidden Confounding	6
Subtype-Aware Registration of Longitudinal Electronic Health Records	6
Conditional Probability Tensor Decompositions for Multivariate Categorical Response Regression	6
Genetically Informed Brain Parcellation Through Structured Multi-Task Modeling	6
Differentially Private Sliced Inverse Regression in the Federated Paradigm	6
Deep Mutual Density Ratio Estimation with Bregman Divergence and Its Applications	6
Fair Coins Tend to Land on the Same Side They Started: Evidence from 350,757 Flips	6
Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests	6
Bayesian Inference Using the Proximal Mapping: Uncertainty Quantification Under Varying Dimensionality	6
Inference in Heavy-Tailed Nonstationary Multivariate Time Series	6
Compositional Graphical Lasso Resolves the Impact of Parasitic Infection on Gut Microbial Interaction Networks in a Zebrafish Model	6
PCABM: Pairwise Covariates-Adjusted Block Model for Community Detection	6
Enhanced Response Envelope via Envelope Regularization	6
High-Dimensional Time Series Segmentation via Factor-Adjusted Vector Autoregressive Modeling	6
High-Dimensional Knockoffs Inference for Time Series Data	6
When Does Bottom-Up Beat Top-Down in Hierarchical Community Detection?	5
Partially Exchangeable Stochastic Block Models for (Node-Colored) Multilayer Networks	5
Statistical Learning for Individualized Asset Allocation	5
Operationalizing Legislative Bodies: A Methodological and Empirical Perspective with a Bayesian Approach	5
An Implementation-Friendly Model-Agnostic Approach for Process Data Analysis	5
Adapting to Noise Tails in Private Linear Regression	5
Interpretable Scalar-on-Image Linear Regression Models via the Generalized Dantzig Selector	5
Variable Significance Testing for the Deep Cox Model	5
Semi-Supervised Triply Robust Inductive Transfer Learning	5
Estimating Higher-Order Mixed Memberships via the l2,∞ Tensor Perturbation Bound	5
Heterogeneous Gene Network Estimation for Single-Cell Transcriptomic Data via a Joint Regularized Deep Neural Network	5
Power of the lack-of-fit test in designed experiments: Guidance on sample size and the distribution of replicates	5
Controlled Epidemiological Studies	5
Efficient Stochastic Generators with Spherical Harmonic Transformation for High-Resolution Global Climate Simulations from CESM2-LENS2	5
Skeleton Clustering: Dimension-Free Density-Aided Clustering	5
Calibrated Model Criticism Using Split Predictive Checks	5
On the Identifying Power of Generalized Monotonicity for Average Treatment Effects	5
Optimizing Sequential Decision Rules for Prostate Cancer Biopsy Management: A Multi-Objective Statistical Framework	5
Kernel Spectral Joint Embeddings for High-Dimensional Noisy Datasets Using Duo-Landmark Integral Operators	5
Neural Networks for Geospatial Data	5
Testing Elliptical Models in High Dimensions	5
Accommodating Time-Varying Heterogeneity in Risk Estimation under the Cox Model: A Transfer Learning Approach	5
Estimation and Inference for Nonparametric Expected Shortfall Regression over RKHS	5
Nonparametric Bootstrap Inference for the Eigenvalues of Geophysical Tensors	5
Graphical Model Inference with Erosely Measured Data	5
Reinforcement Learning in Latent Heterogeneous Environments	5
Testing Simultaneous Diagonalizability	5
Tests for Large-Dimensional Shape Matrices via Tyler’s M Estimators	5
Cohesion and Repulsion in Bayesian Distance Clustering	5
Fast and Flexible Emulation of Spatial Extremes Processes via Variational Autoencoders	5
Monte Carlo Inference for Semiparametric Bayesian Regression	5
A Bayesian Nonparametric Approach to Mediation and Spillover Effects with Multiple Mediators in Cluster-Randomized Trials	5
On Large-Scale System of Sparse Linear Equations with Tree Structures and its Applications to Fiber Optic Networks	5
Efficient Distributed Learning over Decentralized Networks with Convoluted Support Vector Machine	5
Ridge Regression Under Dense Factor Augmented Models	5
Mini-batch Estimation for Deep Cox Models: Statistical Foundations and Practical Guidance	5
Scalable Calibration of Individual-Based Epidemic Models through Categorical Approximations	5