| Applied regression and multilevel/hierarchical models A Gelman, J Hill Cambridge University Press, 2006 | 655 | 2006 |
| 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 | 624 | 2014 |
| Probing genetic overlap among complex human phenotypes A Rzhetsky, D Wajngurt, N Park, T Zheng Proceedings of the National Academy of Sciences 104 (28), 11694-11699, 2007 | 398 | 2007 |
| Segregation in social networks based on acquaintanceship and trust TA DiPrete, A Gelman, T McCormick, J Teitler, T Zheng American journal of sociology 116 (4), 1234-1283, 2011 | 368 | 2011 |
| Cross-species regulatory network analysis identifies a synergistic interaction between FOXM1 and CENPF that drives prostate cancer malignancy A Aytes, A Mitrofanova, C Lefebvre, MJ Alvarez, M Castillo-Martin, ... Cancer cell 25 (5), 638-651, 2014 | 333 | 2014 |
| Why significant variables aren’t automatically good predictors A Lo, H Chernoff, T Zheng, SH Lo Proceedings of the National Academy of Sciences 112 (45), 13892-13897, 2015 | 307 | 2015 |
| Sparse vector autoregressive modeling RA Davis, P Zang, T Zheng Journal of Computational and Graphical Statistics 25 (4), 1077-1096, 2016 | 277 | 2016 |
| How many people do you know in prison? Using overdispersion in count data to estimate social structure in networks T Zheng, MJ Salganik, A Gelman Journal of the American Statistical Association 101 (474), 409-423, 2006 | 261 | 2006 |
| How many people do you know?: Efficiently estimating personal network size TH McCormick, MJ Salganik, T Zheng Journal of the American Statistical Association 105 (489), 59-70, 2010 | 253 | 2010 |
| A molecular signature predictive of indolent prostate cancer S Irshad, M Bansal, M Castillo-Martin, T Zheng, A Aytes, S Wenske, ... Science translational medicine 5 (202), 202ra122-202ra122, 2013 | 171 | 2013 |
| arm: Data analysis using regression and multilevel/hierarchical models A Gelman, YS Su CRAN: Contributed Packages, 2007 | 169 | 2007 |
| Inference of regulatory gene interactions from expression data using three‐way mutual information J Watkinson, K Liang, X Wang, T Zheng, D Anastassiou Annals of the New York Academy of Sciences 1158 (1), 302-313, 2009 | 96 | 2009 |
| Identification of gene interactions associated with disease from gene expression data using synergy networks J Watkinson, X Wang, T Zheng, D Anastassiou BMC systems biology 2, 1-16, 2008 | 83 | 2008 |
| 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 | 81 | 2015 |
| Genetic-linkage mapping of complex hereditary disorders to a whole-genome molecular-interaction network I Iossifov, T Zheng, M Baron, TC Gilliam, A Rzhetsky Genome research 18 (7), 1150-1162, 2008 | 77 | 2008 |
| Latent surface models for networks using aggregated relational data TH McCormick, T Zheng Journal of the American Statistical Association 110 (512), 1684-1695, 2015 | 70 | 2015 |
| Discovering influential variables: a method of partitions H Chernoff, SH Lo, T Zheng | 67 | 2009 |
| Improved Quantification of Ocean Carbon Uptake by Using Machine Learning to Merge Global Models and pCO2 Data L Gloege, M Yan, T Zheng, GA McKinley Journal of Advances in Modeling Earth Systems 14 (2), e2021MS002620, 2022 | 60 | 2022 |
| Interaction-based feature selection and classification for high-dimensional biological data H Wang, SH Lo, T Zheng, I Hu Bioinformatics 28 (21), 2834-2842, 2012 | 57 | 2012 |
| NKX3.1 Suppresses TMPRSS2–ERG Gene Rearrangement and Mediates Repair of Androgen Receptor–Induced DNA Damage C Bowen, T Zheng, EP Gelmann Cancer research 75 (13), 2686-2698, 2015 | 52 | 2015 |
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityCorreu electrònic verificat a stat.columbia.edu