| Super learner MJ Van der Laan, EC Polley, AE Hubbard Statistical applications in genetics and molecular biology 6 (1), 2007 | 2441 | 2007 |
| Targeted learning: causal inference for observational and experimental data M van der Laan, S Rose Springer Verlag [BOOK], 2011 | 1615 | 2011 |
| Unified methods for censored longitudinal data and causality MJ van der Laan, JM Robins Springer Verlag [BOOK], 2003 | 1309* | 2003 |
| To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health AE Hubbard, J Ahern, NL Fleischer, M Van der Laan, SA Lippman, ... Epidemiology 21 (4), 467-474, 2010 | 1276 | 2010 |
| Targeted maximum likelihood learning MJ Van Der Laan, D Rubin International journal of biostatistics 2 (1), Article 1, 2006 | 1070 | 2006 |
| Survival ensembles T Hothorn, P Bühlmann, S Dudoit, A Molinaro, MJ Van Der Laan Biostatistics 7 (3), 355-373, 2006 | 1016 | 2006 |
| Multiple testing procedures with applications to genomics S Dudoit, MJ van der Laan Springer Verlag [BOOK], 2008 | 950* | 2008 |
| Diagnosing and responding to violations in the positivity assumption ML Petersen, KE Porter, S Gruber, Y Wang, MJ Van Der Laan Statistical methods in medical research 21 (1), 31-54, 2012 | 640 | 2012 |
| Promoting transparency in social science research E Miguel, C Camerer, K Casey, J Cohen, KM Esterling, A Gerber, ... Science 343 (6166), 30-31, 2014 | 569 | 2014 |
| Spinal cord injury facts and figures at a glance National Spinal Cord Injury Statistical Center (No Title), 2021 | 547 | 2021 |
| Super learner in prediction EC Polley, MJ Van der Laan bepress, 2010 | 502 | 2010 |
| Estimation of direct causal effects ML Petersen, SE Sinisi, MJ van der Laan Epidemiology 17 (3), 276-284, 2006 | 490 | 2006 |
| Marginal mean models for dynamic regimes SA Murphy, MJ van der Laan, JM Robins, ... Journal of the American Statistical Association 96 (456), 1410-1423, 2001 | 474 | 2001 |
| The relative performance of ensemble methods with deep convolutional neural networks for image classification C Ju, A Bibaut, M van der Laan Journal of applied statistics 45 (15), 2800-2818, 2018 | 439 | 2018 |
| Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study R Pirracchio, ML Petersen, M Carone, MR Rigon, S Chevret, ... The Lancet Respiratory Medicine 3 (1), 42-52, 2015 | 429 | 2015 |
| A new partitioning around medoids algorithm M Van der Laan, K Pollard, J Bryan Journal of Statistical Computation and Simulation 73 (8), 575-584, 2003 | 391 | 2003 |
| Diaphragm and lubricant gel for prevention of HIV acquisition in southern African women: a randomised controlled trial NS Padian, A van der Straten, G Ramjee, T Chipato, G de Bruyn, ... The Lancet 370 (9583), 251-261, 2007 | 388 | 2007 |
| Why match? Investigating matched case-control study designs with causal effect estimation S Rose, MJ Van Der Laan The international journal of biostatistics 5 (1), 2009 | 380* | 2009 |
| Unified cross-validation methodology for selection among estimators and a general cross-validated adaptive epsilon-net estimator: Finite sample oracle inequalities and examples MJ Van Der Laan, S Dudoit bepress, 2003 | 335 | 2003 |
| Targeted learning in data science MJ Van der Laan, S Rose Springer International Publishing, 2018 | 322 | 2018 |
Katherine S PollardDirector, Gladstone Institute of Data Science & Biotechnology / UCSFgladstone.ucsf.edu의 이메일 확인됨
