Andrew Gelman

A calibrated BISG for inferring race from surname and geolocation

The Piranha Problem: Large Effects Swimming in a Small Pond

Hierarchical Bayesian models to mitigate systematic disparities in prediction with proxy outcomes

Nested Rˆ: Assessing the Convergence of Markov Chain Monte Carlo When Running Many Short Chains

Statistics as a Social Activity: Attitudes toward Amalgamating Evidence

Past, Present and Future of Software for Bayesian Inference

Using leave‐one‐out cross validation (LOO) in a multilevel regression and poststratification (MRP) workflow: A cautionary tale

Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity

Causal Quartets: Different Ways to Attain the Same Average Treatment Effect

What is a standard error?

A Chain as Strong as Its Strongest Link? Understanding the Causes and Consequences of Biases Arising from Selective Analysis and Reporting of Research Results

Toward a taxonomy of trust for probabilistic machine learning

Prediction scoring of data-driven discoveries for reproducible research

Fast Methods for Posterior Inference of Two-Group Normal-Normal Models

The Great Society, Reagan's Revolution, and Generations of Presidential Voting

Two Truths and a Lie” as a Class-Participation Activity

Beyond Vaccination Rates: A Synthetic Random Proxy Metric of Total SARS-CoV-2 Immunity Seroprevalence in the Community

Criticism as asynchronous collaboration: An example from social science research

Reconciling Evaluations of the Millennium Villages Project

Inference from Nonrandom Samples Using Bayesian Machine Learning

Bayesian Hierarchical Stacking: Some Models Are (Somewhere) Useful

Routine Hospital-based SARS-CoV-2 Testing Outperforms State-based Data in Predicting Clinical Burden

A Proposal for Informative Default Priors Scaled by the Standard Error of Estimates

What are the Most Important Statistical Ideas of the Past 50 Years?

Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data

Publisher Correction: Bayesian statistics and modelling

Failure and Success in Political Polling and Election Forecasting

Voter Registration Databases and MRP: Toward the Use of Large-Scale Databases in Public Opinion Research

Large-Scale Replication Projects in Contemporary Psychological Research

Multiple Perspectives on Inference for Two Simple Statistical Scenarios

Visualization in Bayesian Workflow

R-squared for Bayesian Regression Models

Comment on “Post-hoc Power Using Observed Estimate of Effect Size is too Noisy to be Useful”

Benefits and limitations of randomized controlled trials: A commentary on Deaton and Cartwright

Disentangling Bias and Variance in Election Polls

Learning from and Responding to Statistical Criticism

Comment: Consensus Monte Carlo using expectation propagation

Cook, Gelman, and Rubin (2006

Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs

Beyond Subjective and Objective in Statistics

Some Natural Solutions to the p -Value Communication Problem—and Why They Won’t Work

Fitting Bayesian item response models in Stata and Stan

Introducing the StataStan Interface for Fast, Complex Bayesian Modeling Using Stan

Stan : A Probabilistic Programming Language

19 Things We Learned from the 2016 Election

The 2008 Election: A Preregistered Replication Analysis

Rejoinder: How Special was 2016?

Increasing Transparency Through a Multiverse Analysis

Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC

COMMENTARY ON “CRISIS IN SCIENCE? OR CRISIS IN STATISTICS! MIXED MESSAGES IN STATISTICS WITH IMPACT ON SCIENCE”

A Model-Based Approach to Climate Reconstruction Using Tree-Ring Data

Stan

Incorporating the sampling design in weighting adjustments for panel attrition

Simulation-efficient shortest probability intervals

Hierarchical Models for Causal Effects

Weakly Informative Prior for Point Estimation of Covariance Matrices in Hierarchical Models

Bayesian and Frequentist Regression Methods

Evidence on the deleterious impact of sustained use of polynomial regression on causal inference

Difficulty of selecting among multilevel models using predictive accuracy

The State of the Art in Causal Inference: Some Changes Since 1972

Statistical Graphics for Survey Weights

The statistical crisis in science: data-dependent analysis--a "garden of forking paths"--explains why many statistically significant comparisons don't hold up

Strength Under Pressure/A World without Statistics

Posterior Distribution: Introduction

Forecasting elections with non-representative polls

Comment

When Do Stories Work? Evidence and Illustration in the Social Sciences

The Connection Between Varying Treatment Effects and the Crisis of Unreplicable Research

Hierarchical Models for Estimating State and Demographic Trends in US Death Penalty Public Opinion

Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches

Estimation and Accuracy after Model Selection Comment

On the stationary distribution of iterative imputations

The Twentieth-Century Reversal: How Did the Republican States Switch to the Democrats and Vice Versa?

Discussion: Difficulties in making inferences about scientific truth from distributions of published p-values

Ethics and Statistics: It's Too Hard to Publish Criticisms and Obtain Data for Republication

Understanding predictive information criteria for Bayesian models

Inherent difficulties of non-Bayesian likelihood-based inference, as revealed by an examination of a recent book by Aitkin

Interrogating p -values

A Nondegenerate Penalized Likelihood Estimator for Variance Parameters in Multilevel Models

Deep Interactions with MRP: Election Turnout and Voting Patterns Among Small Electoral Subgroups

Rejoinder: The Anti-Bayesian Moment and Its Passing

Not Only Defended But Also Applied”: The Perceived Absurdity of Bayesian Inference

Two simple examples for understanding posterior p-values whose distributions are far from uniform

Infovis and Statistical Graphics: Different Goals, Different Looks

A Practical Guide to Measuring Social Structure Using Indirectly Observed Network Data

Preregistration of Studies and Mock Reports

Tradeoffs in Information Graphics

Commentary

Rejoinder to discussion of ‘Philosophy and the practice of Bayesian statistics’

Does the US Media Have a Liberal Bias?

Why We (Usually) Don't Have to Worry About Multiple Comparisons

LETTERS TO THE EDITOR: Responses to Gelman

Causality and Statistical Learning Counterfactuals and Causal Inference: Methods and Principles for Social Research . By Stephen L. Morgan and Christopher Winship. New York: Cambridge University Press, 2007. Pp. xiii+319. Causality: Models, Reasoning, and Inference , 2d ed. By Judea Pearl. Cambridge: Cambridge University Press, 2009. Pp. xix+464. Causal Models: How People Think About the World and Its Alternatives . By Steven A. Sloman. Oxford: Oxford University Press, 2005. Pp. xi+212.

Ethics and Statistics

Going beyond the book: towards critical reading in statistics teaching

Segregation in Social Networks Based on Acquaintanceship and Trust

Multiple Imputation with Diagnostics ( mi ) in R : Opening Windows into the Black Box

Why Tables Are Really Much Better Than Graphs

Induction and Deduction in Baysian Data Analysis

Rejoinder

Protecting Minorities in Large Binary Elections: A Test of Storable Votes Using Field Data

Comment on Article by Robert

Bursts: The Hidden Pattern Behind Everything We Do

Public Opinion on Health Care Reform

WHAT IS THE PROBABILITY YOUR VOTE WILL MAKE A DIFFERENCE?

Bayesian Combination of State Polls and Election Forecasts

Comments on ‘The BUGS project: Evolution, critique and future directions’

Bridges between deterministic and probabilistic models for binary data

A statistician's perspective on “Mostly Harmless Econometrics: An Empiricist's Companion”, by Joshua D. Angrist and Jörn-Steffen Pischke

Comment

Commentary —Discussion of the Article “Website Morphing”

Splitting a Predictor at the Upper Quarter or Third and the Lower Quarter or Third

Of Beauty, Sex and Power

Objections to Bayesian statistics

Teaching Bayes to Graduate Students in Political Science, Sociology, Public Health, Education, Economics, …

Reply to Dr. Arrington

Estimating Incumbency Advantage and Its Variation, as an Example of a Before–After Study

Rejoinder

Using Redundant Parameterizations to Fit Hierarchical Models

Methodology as ideology: some comments on Robert Axelrod's The Evolution of Cooperation

Scaling regression inputs by dividing by two standard deviations

An Analysis of the New York City Police Department's “Stop-and-Frisk” Policy in the Context of Claims of Racial Bias

Manipulating and summarizing posterior simulations using random variable objects

Average Predictive Comparisons for Models with Nonlinearity, Interactions, and Variance Components

Struggles with Survey Weighting and Regression Modeling

Struggles with Survey Weighting and Regression Modeling. Rejoinder.

Weighted Classical Variogram Estimation for Data With Clustering

Bayesian Checking of the Second Levels of Hierarchical Models. Comment..

Letter to the editors regarding some papers of Dr. Satoshi Kanazawa

The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant

Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)

Validation of Software for Bayesian Models Using Posterior Quantiles

Multilevel (Hierarchical) Modeling: What It Can and Cannot Do

An experimental study of storable votes

Comment on article by van Dyk et al

How Many People Do You Know in Prison?

Bayesian Measures of Explained Variance and Pooling in Multilevel (Hierarchical) Models

The Boxer, the Wrestler, and the Coin Flip

Evaluation of multilevel decision trees

Output Assessment for Monte Carlo Simulations via the Score Statistic

Comment: Fuzzy and Bayesian p-Values and u-Values

A Simple Scheme to Improve the Efficiency of Referenda

Multiple Imputation for Model Checking: Completed‐Data Plots with Missing and Latent Data

A Course on Teaching Statistics at the University Level

Practical Issues in Implementing and Understanding Bayesian Ideal Point Estimation

Two-Stage Regression and Multilevel Modeling: A Commentary

Direct Data Manipulation for Local Decision Analysis as Applied to the Problem of Arsenic in Drinking Water from Tube Wells in Bangladesh

Using Image and Curve Registration for Measuring the Goodness of Fit of Spatial and Temporal Predictions

Exploratory Data Analysis for Complex Models

Standard Voting Power Indexes Do Not Work: An Empirical Analysis

A Broken System: The Persistent Patterns of Reversals of Death Sentences in the United States

Bayesian Analysis of Serial Dilution Assays

Parameterization and Bayesian Modeling

Bayesian Multilevel Estimation with Poststratification: State-Level Estimates from National Polls

Forming Voting Blocs and Coalitions as a Prisoner's Dilemma: A Possible Theoretical Explanation for Political Instability

A Bayesian Formulation of Exploratory Data Analysis and Goodness‐of‐fit Testing*

Regression Modeling and Meta-Analysis for Decision Making

The mathematics and statistics of voting power

You Can Load a Die, But You Can't Bias a Coin

Let's Practice What We Preach

Bayesian Inference with Probability Matrix Decomposition Models

Poststratification Without Population Level Information on the Poststratifying Variable With Application to Political Polling

Models, assumptions, and model checking in ecological regressions

Type S error rates for classical and Bayesian single and multiple comparison procedures

Bayesian probabilistic extensions of a deterministic classification model

Case Studies in Bayesian Statistics, Vol. IV

[Optimization Transfer Using Surrogate Objective Functions]: Discussion

Some Class-Participation Demonstrations for Introductory Probability and Statistics

Should we take measurements at an intermediate design point?

Discussion

A method for quantifying artefacts in mapping methods illustrated by application to headbanging

All maps of parameter estimates are misleading

Analysis of Local Decisions Using Hierarchical Modeling, Applied to Home Radon Measurement and Remediation

Evaluating and Using Statistical Methods in the Social Sciences

General Methods for Monitoring Convergence of Iterative Simulations

Not Asked and Not Answered: Multiple Imputation for Multiple Surveys: Rejoinder

Rejoinder

Simulating normalizing constants: from importance sampling to bridge sampling to path sampling

Markov Chain Monte Carlo in Practice: A Roundtable Discussion

Some Class-Participation Demonstrations for Decision Theory and Bayesian Statistics

Student Projects on Statistical Literacy and the Media

Estimating the Probability of Events That Have Never Occurred: When Is Your Vote Decisive?

Improving on Probability Weighting for Household Size

Analysis of Nonrandomly Censored Ordered Categorical Longitudinal Data from Analgesic Trials: Comment

Comment

Using Exams for Teaching Concepts in Probability and Statistics. Teacher's Corner.

Physiological Pharmacokinetic Analysis Using Population Modeling and Informative Prior Distributions

Markov chain Monte Carlo methods in biostatistics

Method of Moments Using Monte Carlo Simulation

Avoiding Model Selection in Bayesian Social Research

A Review: Preelection Survey Methodology: Details From Eight Polling Organizations, 1988 and 1992

Enhancing Democracy Through Legislative Redistricting

A Unified Method of Evaluating Electoral Systems and Redistricting Plans

Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable?

[Backcalculation of HIV Infection Rates]: Comment: Assessing Uncertainty in Backprojection

BACKCALCULATION OF HIV-INFECTION RATES - COMMENT AND REJOINDER

Inference from Iterative Simulation Using Multiple Sequences

Systemic Consequences of Incumbency Advantage in U.S. House Elections

Estimating Incumbency Advantage without Bias

Estimating the Electoral Consequences of Legislative Redistricting