| 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 | 2464 | 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 | 1563* | 2009 |
| arm: Data analysis using regression and multilevel/hierarchical models A Gelman, YS Su, M Yajima, J Hill, MG Pittau, J Kerman, T Zheng, V Dorie | 721 | 2014 |
| 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 | 697 | 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 | 332 | 2013 |
| arm: Data analysis using regression and multilevel/hierarchical models A Gelman, YS Su CRAN: Contributed Packages, 2007 | 170 | 2007 |
| On the stationary distribution of iterative imputations J Liu, A Gelman, J Hill, YS Su, J Kropko Biometrika 101 (1), 155-173, 2013 | 147 | 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 | 146 | 2013 |
| Income inequality and partisan voting in the United States A Gelman, L Kenworthy, YS Su Social science quarterly, 1203-1219, 2010 | 123 | 2010 |
| 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 | 97 | 2016 |
| R2jags: A package for running JAGS from R [Computer software manual] YS Su, M Yajima | 97* | 2012 |
| Package ‘arm’ A Gelman, YS Su, M Yajima, J Hill, MG Pittau, J Kerman, T Zheng, V Dorie, ... Data analysis using regression and multilevel/hierarchical models, 2015 | 82 | 2015 |
| 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 | 60 | 2008 |
| 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 | 46 | 2018 |
| R2jags: Using R to Run ‘JAGS'(R package version 0.5-7)[Computer software manual] YS Su, M Yajima | 42* | 2015 |
| 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 | 39 | 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 | 29 | 2018 |
| 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 | 24* | 2015 |
| 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 | 18 | 2022 |
| What do we gain? Combining propensity score methods and multilevel modeling YS Su, J Cortina Combining Propensity Score Methods and Multilevel Modeling, 2009 | 17 | 2009 |
Andrew GelmanProfessor of Statistics and Political Science, Columbia Universityبريد إلكتروني تم التحقق منه على stat.columbia.edu
