| 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 | 2160 | 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 | 1362* | 2009 |
| arm: Data analysis using regression and multilevel/hierarchical models A Gelman http://cran. r-project. org/web/packages/arm, 2011 | 870* | 2011 |
| 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, 1-31, 2011 | 658 | 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 | 269 | 2013 |
| On the stationary distribution of iterative imputations J Liu, A Gelman, J Hill, YS Su, J Kropko Biometrika 101 (1), 155-173, 2013 | 130 | 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 | 126 | 2013 |
| Income inequality and partisan voting in the United States A Gelman, L Kenworthy, YS Su Social Science Quarterly, 1203-1219, 2010 | 115 | 2010 |
| R2jags: A package for running JAGS from R [Computer software manual] YS Su, M Yajima | 94* | 2012 |
| 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 | 83 | 2016 |
| 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 | 59 | 2008 |
| R2jags: Using R to Run ‘JAGS'(R package version 0.5-7)[Computer software manual] YS Su, M Yajima | 43* | 2015 |
| arm: Data Analysis Using Regression and Multilevel/Hierarchical Models, 2020 A Gelman, YS Su, M Yajima, J Hill, MG Pittau, J Kerman, T Zheng URL http://CRAN. R-project. org/package= arm. R package version, 1.3-02, 2018 | 36 | 2018 |
| 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 | 36 | 2016 |
| Arm: data analysis using regression and multilevel/hierarchical models http://CRAN A Gelman, YS Su, M Yajima, J Hill, MG Pittau, J Kerman, T Zheng, V Dorie R-project. org/package= arm, 2015 | 32* | 2015 |
| 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 | 23 | 2018 |
| Economic growth and happiness in China: A Bayesian multilevel age-period-cohort analysis based on the CGSS data 2005–2015 YS Su, D Lien, Y Yao International Review of Economics & Finance 77, 191-205, 2022 | 15 | 2022 |
| What do we gain? Combining propensity score methods and multilevel modeling YS Su, J Cortina Combining Propensity Score Methods and Multilevel Modeling, 2009 | 13 | 2009 |
| 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 | 9 | 2018 |
| A Pattern Recognition Framework for Detecting Changes in Chinese Internet Management System YS Su, Y Ruan, S Sun, Y Chang JOURNAL OF SOCIAL COMPUTING 1 (1), 28-39, 2020 | 6 | 2020 |
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityZweryfikowany adres z stat.columbia.edu
