| Bayesian workflow A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, ... arXiv preprint arXiv:2011.01808, 2020 | 474 | 2020 |
| Improving multilevel regression and poststratification with structured priors Y Gao, L Kennedy, D Simpson, A Gelman Bayesian Analysis 16 (3), 719 - 744, 2021 | 66 | 2021 |
| Know your population and know your model: Using model-based regression and poststratification to generalize findings beyond the observed sample. L Kennedy, A Gelman Psychological methods 26 (5), 547, 2021 | 62 | 2021 |
| Quantifying sentence acceptability measures: Reliability, bias, and variability S Langsford, A Perfors, AT Hendrickson, LA Kennedy, DJ Navarro Glossa: a journal of general linguistics 3 (1), 1-34, 2018 | 55 | 2018 |
| The experiment is just as important as the likelihood in understanding the prior: a cautionary note on robust cognitive modeling L Kennedy, D Simpson, A Gelman Computational Brain & Behavior 2, 210-217, 2019 | 22 | 2019 |
| Using sex and gender in survey adjustment L Kennedy, K Khanna, D Simpson, A Gelman, Y Jia, J Teitler arXiv preprint arXiv:2009.14401, 2020 | 20* | 2020 |
| Modeling public opinion over time and space: Trust in state institutions in Europe, 1989-2019 M Kołczyńska, PC Bürkner, L Kennedy, A Vehtari Survey Research Methods 18 (1), 1-19, 2024 | 17* | 2024 |
| Causal quartets: Different ways to attain the same average treatment effect A Gelman, J Hullman, L Kennedy The American Statistician 78 (3), 267-272, 2024 | 13 | 2024 |
| Year 15 Fragile Families survey weight adjustment LA Kennedy, A Gelman Fragile Families and Child Wellbeing Study, 2018 | 13 | 2018 |
| Not every credible interval is credible: Evaluating robustness in the presence of contamination in Bayesian data analysis LA Kennedy, DJ Navarro, A Perfors, N Briggs Behavior Research Methods 49, 2219-2234, 2017 | 8 | 2017 |
| Bayesian workflow. arXiv 2020 A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, ... arXiv preprint arXiv:2011.01808, 2011 | 7 | 2011 |
| Cross-validatory model selection for Bayesian autoregressions with exogenous regressors A Cooper, D Simpson, L Kennedy, C Forbes, A Vehtari Bayesian Analysis 1 (1), 2024 | 6 | 2024 |
| Using leave‐one‐out cross validation (LOO) in a multilevel regression and poststratification (MRP) workflow: A cautionary tale S Kuh, L Kennedy, Q Chen, A Gelman Statistics in Medicine 43 (5), 953-982, 2024 | 5 | 2024 |
| Treatment effect estimation with Multilevel Regression and Poststratification Y Gao, L Kennedy, D Simpson arXiv preprint arXiv:2102.10003, 2021 | 4 | 2021 |
| Bayesian cross-validation by parallel Markov chain Monte Carlo A Cooper, A Vehtari, C Forbes, D Simpson, L Kennedy Statistics and Computing 34 (4), 119, 2024 | 3 | 2024 |
| The State of Poverty and Disadvantage in New York City S Collyer, M Maury, L Bushman-Copp, I Garfinkel, L Kennedy, ... Robin Hood, 2020 | 2 | 2020 |
| The Youngest New Yorkers: The Early Childhood Poverty Tracker KM Neckerman, J Brooks-Gunn, E Doran, L Kennedy, M Maury, ... Robin Hood, 2019 | 2 | 2019 |
| The state of poverty and disadvantage in New York City C Wimer, S Collyer, I Garfinkel, L Kennedy, M Maury, KM Neckerman, ... Robin Hood, 2018 | 2 | 2018 |
| Improving Survey Inference in Two-phase Designs Using Bayesian Machine Learning X Wang, L Kennedy, Q Chen arXiv preprint arXiv:2306.04119, 2023 | 1 | 2023 |
| Model validation for aggregate inferences in out-of-sample prediction L Kennedy, A Vehtari, A Gelman arXiv preprint arXiv:2312.06334, 2023 | | 2023 |
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityVerifisert e-postadresse på stat.columbia.edu
