Peter M. Aronow

2.7k total citations · 2 hit papers
46 papers, 1.4k citations indexed

About

Peter M. Aronow is a scholar working on Statistics and Probability, Sociology and Political Science and Political Science and International Relations. According to data from OpenAlex, Peter M. Aronow has authored 46 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Statistics and Probability, 14 papers in Sociology and Political Science and 7 papers in Political Science and International Relations. Recurrent topics in Peter M. Aronow's work include Advanced Causal Inference Techniques (18 papers), Statistical Methods and Bayesian Inference (13 papers) and Statistical Methods and Inference (12 papers). Peter M. Aronow is often cited by papers focused on Advanced Causal Inference Techniques (18 papers), Statistical Methods and Bayesian Inference (13 papers) and Statistical Methods and Inference (12 papers). Peter M. Aronow collaborates with scholars based in United States, Switzerland and China. Peter M. Aronow's co-authors include Hana Shepherd, Elizabeth Levy Paluck, Donald P. Green, Cyrus Samii, Lauren E. Pinson, Jonathon Baron, Mary C. McGrath, Joel A. Middleton, Allison Carnegie and Joshua Kalla and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Peter M. Aronow

44 papers receiving 1.3k citations

Hit Papers

Changing climates of conflict: A social network experimen... 2016 2026 2019 2022 2016 2019 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Peter M. Aronow United States 19 641 336 294 196 138 46 1.4k
Adam Glynn United States 15 566 0.9× 309 0.9× 276 0.9× 169 0.9× 213 1.5× 33 1.3k
Jake Bowers United States 11 653 1.0× 479 1.4× 114 0.4× 227 1.2× 100 0.7× 27 1.1k
Graeme Blair United States 14 926 1.4× 445 1.3× 349 1.2× 56 0.3× 172 1.2× 23 1.4k
Ian Brunton‐Smith United Kingdom 20 1.7k 2.6× 343 1.0× 44 0.1× 129 0.7× 111 0.8× 57 2.2k
Kevin Mullinix United States 12 949 1.5× 553 1.6× 36 0.1× 322 1.6× 112 0.8× 20 1.5k
Godfríed Engbersen Netherlands 18 1.2k 1.8× 219 0.7× 61 0.2× 108 0.6× 91 0.7× 81 1.6k
Alexander Coppock United States 22 1.7k 2.6× 1.1k 3.1× 178 0.6× 570 2.9× 266 1.9× 42 2.8k
Michael Sances United States 16 701 1.1× 515 1.5× 34 0.1× 162 0.8× 248 1.8× 40 1.3k
John G. Bullock United States 11 735 1.1× 644 1.9× 29 0.1× 338 1.7× 101 0.7× 17 1.3k
Michele F. Margolis United States 12 657 1.0× 325 1.0× 29 0.1× 154 0.8× 93 0.7× 25 1.1k

Countries citing papers authored by Peter M. Aronow

Since Specialization
Citations

This map shows the geographic impact of Peter M. Aronow's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Peter M. Aronow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter M. Aronow more than expected).

Fields of papers citing papers by Peter M. Aronow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter M. Aronow. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Peter M. Aronow. The network helps show where Peter M. Aronow may publish in the future.

Co-authorship network of co-authors of Peter M. Aronow

This figure shows the co-authorship network connecting the top 25 collaborators of Peter M. Aronow. A scholar is included among the top collaborators of Peter M. Aronow based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peter M. Aronow. Peter M. Aronow is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Ye, et al.. (2025). Design-based inference for spatial experiments under unknown interference. The Annals of Applied Statistics. 19(1). 3 indexed citations
2.
Middleton, Joel A., et al.. (2024). Exact Bias Correction for Linear Adjustment of Randomized Controlled Trials. Econometrica. 92(5). 1503–1519. 3 indexed citations
3.
Carlson, Jake, et al.. (2023). Dyadic Clustering in International Relations. Political Analysis. 32(2). 186–198. 2 indexed citations
4.
Aronow, Peter M. & Benjamin T. Miller. (2019). Foundations of Agnostic Statistics. Cambridge University Press eBooks. 25 indexed citations
5.
Aronow, Peter M., Dean Karlan, & Lauren E. Pinson. (2018). The effect of images of Michelle Obama’s face on trick-or-treaters’ dietary choices: A randomized control trial. PLoS ONE. 13(1). e0189693–e0189693. 3 indexed citations
6.
Paluck, Elizabeth Levy, Hana Shepherd, & Peter M. Aronow. (2016). Changing climates of conflict: A social network experiment in 56 schools. Proceedings of the National Academy of Sciences. 113(3). 566–571. 307 indexed citations breakdown →
7.
McGrath, Mary C., et al.. (2016). Chocolate scents and product sales: a randomized controlled trial in a Canadian bookstore and café. SpringerPlus. 5(1). 670–670. 3 indexed citations
8.
Aronow, Peter M.. (2016). Data-Adaptive Causal Effects and Superefficiency. SHILAP Revista de lepidopterología. 4(2). 1 indexed citations
9.
Kalla, Joshua & Peter M. Aronow. (2015). Editorial Bias in Crowd-Sourced Political Information. PLoS ONE. 10(9). e0136327–e0136327. 7 indexed citations
10.
Aronow, Peter M. & Forrest W. Crawford. (2015). Nonparametric identification for respondent-driven sampling. Statistics & Probability Letters. 106. 100–102. 7 indexed citations
11.
Aronow, Peter M., Alexander Coppock, F. W. Crawford, & Donald P. Green. (2015). Combining List Experiment and Direct Question Estimates of Sensitive Behavior Prevalence. Journal of Survey Statistics and Methodology. 3(1). 43–66. 61 indexed citations
12.
Aronow, Peter M., Jonathon Baron, & Lauren E. Pinson. (2015). A Note on Dropping Experimental Subjects Who Fail a Manipulation Check. SSRN Electronic Journal. 19 indexed citations
13.
Aronow, Peter M. & Cyrus Samii. (2015). Does Regression Produce Representative Estimates of Causal Effects?. American Journal of Political Science. 60(1). 250–267. 9 indexed citations
14.
Aronow, Peter M. & Joel A. Middleton. (2013). A Class of Unbiased Estimators of the Average Treatment Effect in Randomized Experiments. SHILAP Revista de lepidopterología. 1(1). 135–154. 42 indexed citations
15.
Aronow, Peter M. & Allison Carnegie. (2013). Beyond LATE: Estimation of the Average Treatment Effect with an Instrumental Variable. Political Analysis. 21(4). 492–506. 41 indexed citations
16.
Aronow, Peter M. & Cyrus Samii. (2012). Conservative variance estimation for sampling designs with zero pairwise inclusion probabilities. 39(1). 231–241. 6 indexed citations
17.
Samii, Cyrus & Peter M. Aronow. (2012). Estimating Average Causal Effects Under General Interference. The Annals of Applied Statistics. 26 indexed citations
18.
Aronow, Peter M. & Cyrus Samii. (2012). ri: R Package for Performing Randomization-Based Inference for Experiments. 8 indexed citations
19.
Aronow, Peter M.. (2012). A General Method for Detecting Interference Between Units in Randomized Experiments. Sociological Methods & Research. 41(1). 3–16. 4 indexed citations
20.
Aronow, Peter M. & Donald Lee. (2012). Interval estimation of population means under unknown but bounded probabilities of sample selection. Biometrika. 100(1). 235–240. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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