| Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009-2014 C Rhee, R Dantes, L Epstein, DJ Murphy, CW Seymour, TJ Iwashyna, ... Jama 318 (13), 1241-1249, 2017 | 1575 | 2017 |
| 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 | 588 | 2012 |
| Collaborative double robust targeted maximum likelihood estimation MJ van der Laan, S Gruber The international journal of biostatistics 6 (1), 2010 | 234 | 2010 |
| tmle: an R package for targeted maximum likelihood estimation S Gruber, M Van Der Laan Journal of Statistical Software 51, 1-35, 2012 | 232 | 2012 |
| Targeted minimum loss based estimation of causal effects of multiple time point interventions MJ van der Laan, S Gruber The international journal of biostatistics 8 (1), 2012 | 193 | 2012 |
| A targeted maximum likelihood estimator of a causal effect on a bounded continuous outcome S Gruber, MJ van der Laan The International Journal of Biostatistics 6 (1), 2010 | 181 | 2010 |
| Targeted maximum likelihood estimation for dynamic and static longitudinal marginal structural working models M Petersen, J Schwab, S Gruber, N Blaser, M Schomaker, ... Journal of causal inference 2 (2), 147-185, 2014 | 166 | 2014 |
| The relative performance of targeted maximum likelihood estimators KE Porter, S Gruber, MJ Van Der Laan, JS Sekhon The international journal of biostatistics 7 (1), 0000102202155746791308, 2011 | 132 | 2011 |
| An application of collaborative targeted maximum likelihood estimation in causal inference and genomics S Gruber, MJ van der Laan The International Journal of Biostatistics 6 (1), 2010 | 110 | 2010 |
| Development and validation of an automated HIV prediction algorithm to identify candidates for pre-exposure prophylaxis: a modelling study DS Krakower, S Gruber, K Hsu, JT Menchaca, JC Maro, BA Kruskal, ... The Lancet HIV 6 (10), e696-e704, 2019 | 107 | 2019 |
| Relative performance of propensity score matching strategies for subgroup analyses SV Wang, Y Jin, B Fireman, S Gruber, M He, R Wyss, HJ Shin, Y Ma, ... American journal of epidemiology 187 (8), 1799-1807, 2018 | 75 | 2018 |
| Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets S Gruber, RW Logan, I Jarrín, S Monge, MA Hernán Statistics in medicine 34 (1), 106-117, 2015 | 73 | 2015 |
| One-step targeted minimum loss-based estimation based on universal least favorable one-dimensional submodels M van der Laan, S Gruber The international journal of biostatistics 12 (1), 351-378, 2016 | 68 | 2016 |
| Empirical performance of a new user cohort method: lessons for developing a risk identification and analysis system PB Ryan, MJ Schuemie, S Gruber, I Zorych, D Madigan Drug safety 36, 59-72, 2013 | 65 | 2013 |
| Targeted maximum likelihood estimation: A gentle introduction S Gruber, MJ Van Der Laan bepress, 2009 | 63 | 2009 |
| Application of machine-learning to predict early spontaneous preterm birth among nulliparous non-Hispanic black and white women A Weber, GL Darmstadt, S Gruber, ME Foeller, SL Carmichael, ... Annals of epidemiology 28 (11), 783-789. e1, 2018 | 60 | 2018 |
| Variable selection for confounder control, flexible modeling and collaborative targeted minimum loss-based estimation in causal inference ME Schnitzer, JJ Lok, S Gruber The international journal of biostatistics 12 (1), 97-115, 2016 | 50 | 2016 |
| Targeted minimum loss based estimation of an intervention specific mean outcome MJ van der Laan, S Gruber bepress, 2011 | 46 | 2011 |
| Ultra-short-course antibiotics for patients with suspected ventilator-associated pneumonia but minimal and stable ventilator settings M Klompas, L Li, JT Menchaca, S Gruber, ... Clinical Infectious Diseases 64 (7), 870-876, 2017 | 44 | 2017 |
| Practical considerations for specifying a super learner RV Phillips, MJ Van Der Laan, H Lee, S Gruber International Journal of Epidemiology 52 (4), 1276-1285, 2023 | 42 | 2023 |
