| A weakly informative default prior distribution for logistic and other regression models A Gelman, A Jakulin, MG Pittau, YS Su The Annals of Applied Statistics 2 (4), 1360-1383, 2008 | 1705 | 2008 |
| R Package "R2jags: A Package for Running jags from R" YS Su, M Yajima R package version 0.03-08, URL http://CRAN. R-project. org/package= R2jags, 2009 | 911* | 2009 |
| R Package "arm: data analysis using regression and multilevel/hierarchical models" A Gelman, YS Su | 645* | 2008 |
| Multiple imputation with diagnostics (mi) in R: Opening windows into the black box YS Su, A Gelman, J Hill, M Yajima Journal of Statistical Software 45 (1), 1-31, 2011 | 569 | 2011 |
| The effect of institutional proximity in non-local university–industry collaborations: An analysis based on Chinese patent data W Hong, YS Su Research Policy 42 (2), 454-464, 2013 | 203 | 2013 |
| Income inequality and partisan voting in the United States A Gelman, L Kenworthy, YS Su Social Science Quarterly, 1203-1219, 2010 | 100 | 2010 |
| On the stationary distribution of iterative imputations J Liu, A Gelman, J Hill, YS Su, J Kropko Biometrika 101 (1), 155-173, 2013 | 95 | 2013 |
| Assessing lack of common support in causal inference using Bayesian nonparametrics: Implications for evaluating the effect of breastfeeding on children's cognitive outcomes J Hill, YS Su The Annals of Applied Statistics, 1386-1420, 2013 | 78 | 2013 |
| It’s easy to produce chartjunk using Microsoft Excel 2007 but hard to make good graphs YS Su Computational Statistics & Data Analysis 52 (10), 4594-4601, 2008 | 45 | 2008 |
| Could more civil society involvement increase public support for climate policy-making? Evidence from a survey experiment in China T Bernauer, R Gampfer, T Meng, YS Su Global Environmental Change 40, 1-12, 2016 | 44 | 2016 |
| The mechanism of how design failures cause unsafe behavior: the cognitive reliability and error analysis method (CREAM) PC Liao, X Luo, T Wang, Y Su Procedia Engineering 145, 715-722, 2016 | 25 | 2016 |
| Development of data-driven influence model to relate the workplace environment to human error PC Liao, H Shi, Y Su, X Luo Journal of construction engineering and management 144 (3), 04018003, 2018 | 13 | 2018 |
| What do we gain? Combining propensity score methods and multilevel modeling YS Su, J Cortina Combining Propensity Score Methods and Multilevel Modeling, 2009 | 9 | 2009 |
| Causal inference of repeated observations: A synthesis of the propensity score methods and multilevel modeling YS Su Available at polmeth. wustl. edu/retrieve. php, 2008 | 3 | 2008 |
| Estimating the influence of improper workplace environment on human error: Posterior predictive analysis PC Liao, M Liu, YS Su, H Shi, X Luo Advances in Civil Engineering 2018, 2018 | 2 | 2018 |
| 美国、欧盟、中国与拉美双边经贸关系的比较研究 苏毓淞 拉丁美洲研究 36 (3), 26-34, 2014 | 2 | 2014 |
| Multilevel regression and poststratification: An R package A Gelman, M Malecki, D Lee, YS Su | 2 | 2014 |
| Contriving the future by tampering with the past: A deferral tactic in Chinese internet censorship Y SU, S Sun, J Liu SocArXiv, 2019 | 1 | 2019 |
| Weakly informative priors A Gelman, A Jakulin | 1 | 2017 |
| 差序政治信任的城乡比较-基于 2015 年中国城乡社会治理调查数据的实证研究 张小劲， 陈波， 苏毓淞 湘潭大学学报: 哲学社会科学版 41 (6), 32-39, 2017 | 1 | 2017 |
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityZweryfikowany adres z stat.columbia.edu
