LLM-generated corrections to the published research of P. M. Aronow
This site lists corrections to my published research, as generated by large language models and as supervised by me (P. M. Aronow). The works are mine and those of my coauthors. The record shows no consultation with my coauthors, and nothing here speaks for them. The corrections began with an audit that multiple large language models carried out at my request.
This site is still a work in progress. It is subject to change as investigations continue and as models improve.
Almost all text on this website is machine-generated. I have personally reviewed all errors classified as moderate, major or critical, and a portion of those classified as minor or as clarity notes. My review is ongoing. Apart from earlier official corrections that an entry restates, no correction listed here is recorded as officially accepted by my coauthors or by a journal. This is an unofficial resource that is being provided without warranty as a service to the academic community.
The page of each work names the edition that was audited, says what was checked and what was not, and lists the corrections, the most serious first. A correction has a permanent identifier and a severity. It gives the passage as printed, the problem, the evidence, what survives and the corrected passage. Clarity notes are listed separately, and the About page defines them.
Two cautions apply to every page. First, the audit cannot say how many errors it missed. An estimate of its recall—the proportion of all errors it found—would need a benchmark of errors established independently of the models used in the audit, and it has no such benchmark. Second, where no correction is listed, the audit does not find that the work is correct. Where the audit reports no error, at least two reads and the recorded checks raised no error that was confirmed. As part of this verification effort, I have also used large language models to formalize and prove in Lean, a proof assistant, selected mathematical results of my work and the corrections to its mathematical statements, with their counterexamples. The current formal statements and proofs are maintained in llm-audit-lean; each formal target links to its statement and proof. I have not examined these proofs personally. These formalizations were built as part of the verification effort, and are being provided without warranty as a potentially helpful resource. They have not been vetted to the standards of other posted formalizations, e.g., on Palomar. A proof establishes its Lean statement under the stated assumptions. Whether that statement captures the printed or corrected passage depends on a separate comparison with the text.
The audit in numbers
| Works audited (the planned checks were completed for every work; my review continues) | 52 |
|---|---|
| Possible errors examined | 1314 |
| Classified as errors | 796 |
| Critical | 1 |
| Major | 7 |
| Moderate | 109 |
| Minor | 679 |
| Clarity notes | 158 |
| Not confirmed | 212 |
| Undetermined | 87 |
| Outside the scope | 61 |
An entry is classified as an error when independent model checks confirmed it against the published text. Most are Minor (679 of 796: real but inconsequential). Three restate corrections the authors had already published. Neither the number of errors the audit missed nor the number of entries wrongly classified as errors is known.
Listed on this site: 796 corrections, 158 clarity notes, and 2 entries examined and not confirmed, in 52 works.
Works
Books (1)
- Foundations of Agnostic StatisticsP. M. Aronow and Benjamin T. Miller. Cambridge University Press, 2019.126 corrections (8 Moderate, 118 Minor); 24 clarity notes
Articles: theory and methodology (31)
- On the Foundations of the Design-Based ApproachP. M. Aronow, Austin Jang, and Molly Offer-Westort. Political Analysis, 2026.7 corrections (1 Moderate, 6 Minor); 10 clarity notes
- Randomization-based confidence sets for the local average treatment effectP. M. Aronow, Haoge Chang, and Patrick Lopatto. Biometrika, 2026.32 corrections (2 Moderate, 30 Minor); 3 clarity notes
- Design-Based Inference for Spatial Experiments under Unknown InterferenceYe Wang, Cyrus Samii, Haoge Chang, and P. M. Aronow. Annals of Applied Statistics, 2025.43 corrections (10 Moderate, 33 Minor); 6 clarity notes
- Fast computation of exact confidence intervals for randomized experiments with binary outcomesP. M. Aronow, Haoge Chang, and Patrick Lopatto. Journal of Econometrics, 2025.38 corrections (8 Moderate, 30 Minor); 4 clarity notes
- Exact Bias Correction for Linear Adjustment of Randomized Controlled TrialsHaoge Chang, Joel A. Middleton, and P. M. Aronow. Econometrica, 2024.16 corrections (1 Moderate, 15 Minor); 2 clarity notes
- On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information AsymmetrySerena Wang, Stephen Bates, P. M. Aronow, and Michael I. Jordan. AISTATS 2024, 2024.22 corrections (1 Major, 1 Moderate, 20 Minor); 2 clarity notes
- Inference in Spatial Experiments with Interference using the SpatialEffect PackageCyrus Samii, Ye Wang, Jonathan Sullivan, and P. M. Aronow. Journal of Agricultural, Biological, and Environmental Statistics, 2023.21 corrections (1 Major, 3 Moderate, 17 Minor); 1 clarity note
- Listwise Deletion in High DimensionsJ. Sophia Wang and P. M. Aronow. Political Analysis, 2023.9 corrections (9 Minor); 2 clarity notes
- Average treatment effects in the presence of unknown interferenceFredrik Sävje, P. M. Aronow, and Michael G. Hudgens. Annals of Statistics, 2021.23 corrections (23 Minor); 8 clarity notes
- A Note on Dropping Experimental Subjects who Fail a Manipulation CheckP. M. Aronow, Jonathon Baron, and Lauren Pinson. Political Analysis, 2019.20 corrections (4 Moderate, 16 Minor); 5 clarity notes
- Confidence Intervals for Linear Unbiased Estimators under Constrained DependenceP. M. Aronow, Forrest W. Crawford, and Jose R. Zubizarreta. Electronic Journal of Statistics, 2018.17 corrections (1 Critical, 2 Moderate, 14 Minor); 1 clarity note
- Identification of homophily and preferential recruitment in respondent-driven samplingForrest W. Crawford, P. M. Aronow, Li Zeng, and Jianghong Li. American Journal of Epidemiology, 2018.11 corrections (3 Moderate, 8 Minor); 1 clarity note
- Estimating Average Causal Effects Under General Interference, with Application to a Social Network ExperimentP. M. Aronow and Cyrus Samii. Annals of Applied Statistics, 2017.21 corrections (4 Moderate, 17 Minor); 7 clarity notes
- The Regression Discontinuity Design under Interference: A Local Randomization-Based ApproachP. M. Aronow, Nicole E. Basta, and M. Elizabeth Halloran. Observational Studies, 2017.7 corrections (1 Moderate, 6 Minor)
- Data-Adaptive Causal Effects and SuperefficiencyP. M. Aronow. Journal of Causal Inference, 2016.5 corrections (1 Moderate, 4 Minor); 1 clarity note
- Does Regression Produce Representative Estimates of Causal Effects?P. M. Aronow and Cyrus Samii. American Journal of Political Science, 2016.14 corrections (3 Moderate, 11 Minor); 4 clarity notes
- Research Note: A More Powerful Test Statistic for Reasoning about Interference between UnitsJake Bowers, Mark M. Fredrickson, and P. M. Aronow. Political Analysis, 2016.11 corrections (2 Moderate, 9 Minor)
- Cluster-Robust Variance Estimation for Dyadic DataP. M. Aronow, Cyrus Samii, and Valentina A. Assenova. Political Analysis, 2015.21 corrections (4 Moderate, 17 Minor); 2 clarity notes
- Combining List Experiment and Direct Question Estimates of Sensitive Behavior PrevalenceP. M. Aronow, Alexander Coppock, Forrest W. Crawford, and Donald P. Green. Journal of Survey Statistics and Methodology, 2015.10 corrections (1 Moderate, 9 Minor); 4 clarity notes
- Nonparametric Identification for Respondent-Driven SamplingP. M. Aronow and Forrest W. Crawford. Statistics and Probability Letters, 2015.2 corrections (2 Minor); 2 clarity notes
- Unbiased Estimation of the Average Treatment Effect in Cluster-Randomized ExperimentsJoel A. Middleton and P. M. Aronow. Statistics, Politics and Policy, 2015.9 corrections (1 Moderate, 8 Minor); 3 clarity notes
- A Note on Close Elections and Regression Analysis of the Party Incumbency AdvantageP. M. Aronow, David R. Mayhew, and Winston Lin. Statistics, Politics and Policy, 2014.8 corrections (4 Moderate, 4 Minor); 2 clarity notes
- Field Experimental Designs for the Study of Media EffectsDonald P. Green, Brian R. Calfano, and P. M. Aronow. Political Communication, 2014.19 corrections (19 Minor); 3 clarity notes
- Sharp bounds on the variance in randomized experimentsP. M. Aronow, Donald P. Green, and Donald K. K. Lee. Annals of Statistics, 2014.9 corrections (1 Moderate, 8 Minor); 2 clarity notes
- A Class of Unbiased Estimators of the Average Treatment Effect in Randomized ExperimentsP. M. Aronow and Joel A. Middleton. Journal of Causal Inference, 2013.8 corrections (3 Moderate, 5 Minor); 2 clarity notes
- Beyond LATE: Estimation of the Average Treatment Effect with an Instrumental VariableP. M. Aronow and Allison Carnegie. Political Analysis, 2013.23 corrections (4 Moderate, 19 Minor); 3 clarity notes
- Conservative Variance Estimation for Sampling Designs with Zero Pairwise Inclusion ProbabilitiesP. M. Aronow and Cyrus Samii. Survey Methodology, 2013.9 corrections (1 Moderate, 8 Minor); 5 clarity notes
- Interval Estimation of Population Means under Unknown but Bounded Probabilities of Sample SelectionP. M. Aronow and Donald K. K. Lee. Biometrika, 2013.8 corrections (2 Moderate, 6 Minor); 4 clarity notes
- Sharp Bounds for Complier Average Potential Outcomes in Experiments with Noncompliance and Incomplete ReportingP. M. Aronow and Donald P. Green. Statistics and Probability Letters, 2013.4 corrections (4 Minor); 2 clarity notes
- A General Method for Detecting Interference Between Units in Randomized ExperimentsP. M. Aronow. Sociological Methods and Research, 2012.11 corrections (2 Moderate, 9 Minor); 2 clarity notes
- On Equivalencies Between Design-Based and Regression-Based Variance Estimators for Randomized ExperimentsCyrus Samii and P. M. Aronow. Statistics and Probability Letters, 2012.4 corrections (4 Minor); 2 clarity notes
Articles: empirics (12)
- Dyadic Clustering in International RelationsJacob Carlson, Trevor Incerti, and P. M. Aronow. Political Analysis, 2024.16 corrections (5 Moderate, 11 Minor); 3 clarity notes
- On the reliability of published findings using the regression discontinuity design in political scienceDrew Stommes, P. M. Aronow, and Fredrik Sävje. Research and Politics, 2023.14 corrections (1 Major, 2 Moderate, 11 Minor); 2 clarity notes
- The Negative Consequences of Informing Voters about Deepfakes: Evidence from Two Survey ExperimentsJohn Ternovski, Joshua Kalla, and P. M. Aronow. Journal of Online Trust and Safety, 2022.18 corrections (18 Minor); 1 clarity note
- The Effect of Images of Michelle Obama's Face on Trick-or-Treaters' Dietary Choices: A Randomized Control TrialP. M. Aronow, Dean Karlan, and Lauren E. Pinson. PLOS ONE, 2018.2 corrections (1 Major, 1 Minor); 2 clarity notes
- Information and Access to United Nations Diplomatic MissionsP. M. Aronow, Molly Offer-Westort, Lauren E. Pinson, and Ana C. Perez-Gea. Applied Economics Letters, 2017.4 corrections (4 Minor); 2 clarity notes
- Changing Climates of Conflict: A Social Network Experiment in 56 SchoolsElizabeth Levy Paluck, Hana Shepherd, and P. M. Aronow. PNAS, 2016.34 corrections (1 Major, 10 Moderate, 23 Minor); 1 clarity note
- Chocolate Scents and Product Sales: A Randomized Controlled Trial in a Canadian Bookstore and CafeMary C. McGrath, P. M. Aronow, and Vivien Shotwell. SpringerPlus, 2016.4 corrections (1 Moderate, 3 Minor)
- Driving Fatalities on US Presidential Election Days: A ReanalysisFan Zhang and P. M. Aronow. BMC Research Notes, 2016.1 correction (1 Minor); 3 clarity notes
- Ideologically Extreme Candidates in U.S. Presidential Elections, 1948-2012Marty Cohen, Mary C. McGrath, P. M. Aronow, and John Zaller. Annals of the American Academy of Political and Social Science, 2016.9 corrections (9 Minor); 4 clarity notes
- Editorial Bias in Crowd-Sourced Political InformationJoshua L. Kalla and P. M. Aronow. PLOS ONE, 2015.20 corrections (1 Major, 2 Moderate, 17 Minor); 2 clarity notes
- Field Experiments and the Study of Voter TurnoutDonald P. Green, Mary C. McGrath, and P. M. Aronow. Journal of Elections, Public Opinion and Parties, 2013.11 corrections (3 Moderate, 8 Minor); 2 clarity notes
- Does Knowledge of Constitutional Principles Increase Support for Civil Liberties? Results from a Randomized Field ExperimentDonald P. Green, P. M. Aronow, Daniel E. Bergan, Pamela Greene, Celia Paris, and Beth I. Weinberger. Journal of Politics, 2011.23 corrections (1 Moderate, 22 Minor)
Book chapters (2)
- Estimating Causal Effects in Experiments with Network SpilloversStephanie Zonszein, P. M. Aronow, and Cyrus Samii. Handbook of Computational Social Science, 2025.14 corrections (1 Major, 1 Moderate, 12 Minor); 2 clarity notes
- Spillover Effects in Experimental DataP. M. Aronow, Dean Eckles, Cyrus Samii, and Stephanie Zonszein. Advances in Experimental Political Science, 2021.15 corrections (5 Moderate, 10 Minor); 9 clarity notes
Essays, commentary and reports (6)
- Nonparametric identification is not enough, but randomized controlled trials areP. M. Aronow, James M. Robins, Theo Saarinen, Fredrik Sävje, and Jasjeet Sekhon. Observational Studies, 2025.3 corrections (1 Moderate, 2 Minor); 3 clarity notes
- Rejoinder: Nonparametric Identification Is Not Enough, but Randomized Controlled Trials AreP. M. Aronow, James M. Robins, Theo Saarinen, Fredrik Sävje, and Jasjeet Sekhon. Observational Studies, 2025.4 corrections (4 Minor); 1 clarity note
- Gnostic Notes on Temporal ValidityAustin Jang, Molly Offer-Westort, Serena Wang, and P. M. Aronow. Research and Politics, 2024.10 corrections (10 Minor)
- Review of The Book of Why: The New Science of Cause and EffectP. M. Aronow and Fredrik Sävje. Journal of the American Statistical Association, 2020.2 corrections (2 Minor)
- Understanding Ding's Apparent ParadoxP. M. Aronow and Molly R. Offer-Westort. Statistical Science, 2017.2 clarity notes
- Policy Misperceptions and Support for Gun Control LegislationP. M. Aronow and Benjamin T. Miller. The Lancet, 2016.4 corrections (1 Moderate, 3 Minor)
Formal results: 805 whole; 110 restricted; 73 refuted; 33 omitted.
Coverage concerns the identified claim under its stated assumptions. A checked proof establishes the formal statement; correspondence to the published text was reviewed by AI. Repository access is currently required to open the source links.