| A new automated redistricting simulator using Markov chain Monte Carlo B Fifield, M Higgins, K Imai, A Tarr Working Paper. Available at http://imai. princeton. edu/research/files …, 2016 | 171* | 2016 |
| Improving massive experiments with threshold blocking MJ Higgins, F Sävje, JS Sekhon Proceedings of the National Academy of Sciences 113 (27), 7369-7376, 2016 | 83 | 2016 |
| Nitrogen oxides and ozone in urban air: A review of 50 plus years of progress LE Erickson, GL Newmark, MJ Higgins, Z Wang Environmental Progress & Sustainable Energy 39 (6), e13484, 2020 | 50 | 2020 |
| Generalized Full Matching F Sävje, MJ Higgins, JS Sekhon arXiv preprint arXiv:1703.03882, 2017 | 43* | 2017 |
| Sharper p-values for stratified election audits MJ Higgins, RL Rivest, PB Stark Statistics, Politics, and Policy 2 (1), 2011 | 17 | 2011 |
| Does dividing the range by four provide an accurate estimate of a standard deviation in family science research? A teaching editorial WR Schumm, M Higgins, L Lockett, S Huang, N Abdullah, A Asiri, K Clark, ... Marriage & Family Review 53 (1), 1-23, 2017 | 14 | 2017 |
| Blocking estimators and inference under the Neyman-Rubin model MJ Higgins, F Sävje, JS Sekhon arXiv preprint arXiv:1510.01103, 2015 | 9 | 2015 |
| A new method for quantifying network cyclic structure to improve community detection B Moradi-Jamei, H Shakeri, P Poggi-Corradini, MJ Higgins Physica A: Statistical Mechanics and its Applications 561, 125116, 2021 | 7 | 2021 |
| Nitrogen Dioxide and Ozone Pollution in the Chicago Metropolitan Area Z Wang, JL Anthony, LE Erickson, MJ Higgins, GL Newmark Journal of Environmental Protection 11 (08), 551, 2020 | 6 | 2020 |
| Estimating the Standard Deviation From the Range: a Replication of Analysis of Demographic Data Reported in Marriage & Family Review, 2016-2017 WR Schumm, DW Crawford, M Higgins, L Lockett, A AlRashed, ... Marriage & Family Review 54 (8), 777-792, 2018 | 6 | 2018 |
| Detecting Treatment Interference under the K-Nearest-Neighbors Interference Model SH Alzubaidi, MJ Higgins arXiv preprint arXiv:2203.16710, 2022 | 4 | 2022 |
| From one environment to many: The problem of replicability of statistical inferences JJ Higgins, MJ Higgins, J Lin The American Statistician, 1-9, 2020 | 4 | 2020 |
| Estimation of Causal Effects Under K-Nearest Neighbors Interference S Alzubaidi, MJ Higgins arXiv preprint arXiv:2307.15204, 2023 | 3 | 2023 |
| Applications of Integer Programming Methods to Solve Statistical Problems MJ Higgins University of California, Berkeley, 2013 | 2 | 2013 |
| The Benefits of Probability-Proportional-to-Size Sampling in Cluster-Randomized Experiments Y Xiong, MJ Higgins arXiv preprint arXiv:2002.08009, 2020 | 1 | 2020 |
| Hybridized Threshold Clustering for Massive Data J Luo, CV Annakula, AS Kannamareddy, JS Sekhon, WH Hsu, M Higgins arXiv preprint arXiv:1907.02907, 2019 | 1 | 2019 |
| Operating subsidies and transit efficiency: applying new metrics to old problems CD Funk, MJ Higgins, GL Newmark Transportation, 1-20, 2023 | | 2023 |
| Demystifying Statistical Matching Algorithms for Big Data S Weerasingha, MJ Higgins arXiv preprint arXiv:2309.05859, 2023 | | 2023 |
Jasjeet SekhonEugene Meyer Professor of Data Science, Political Science, and Statistics, Yale UniversityVerified email at yale.edu
