Mark J van der Laan, Eric C Polley, Alan E Hubbard. Stat Appl Genet Mol Biol 2007
Times Cited: 535
Times Cited: 535
Times Cited
Times Co-cited
Similarity
Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies.
Megan S Schuler, Sherri Rose. Am J Epidemiol 2017
Megan S Schuler, Sherri Rose. Am J Epidemiol 2017
10
Doubly robust estimation in missing data and causal inference models.
Heejung Bang, James M Robins. Biometrics 2005
Heejung Bang, James M Robins. Biometrics 2005
9
Regularization Paths for Generalized Linear Models via Coordinate Descent.
Jerome Friedman, Trevor Hastie, Rob Tibshirani. J Stat Softw 2010
Jerome Friedman, Trevor Hastie, Rob Tibshirani. J Stat Softw 2010
8
Stacked generalization: an introduction to super learning.
Ashley I Naimi, Laura B Balzer. Eur J Epidemiol 2018
Ashley I Naimi, Laura B Balzer. Eur J Epidemiol 2018
16
Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression.
Daniel Westreich, Justin Lessler, Michele Jonsson Funk. J Clin Epidemiol 2010
Daniel Westreich, Justin Lessler, Michele Jonsson Funk. J Clin Epidemiol 2010
6
Diagnosing and responding to violations in the positivity assumption.
Maya L Petersen, Kristin E Porter, Susan Gruber, Yue Wang, Mark J van der Laan. Stat Methods Med Res 2012
Maya L Petersen, Kristin E Porter, Susan Gruber, Yue Wang, Mark J van der Laan. Stat Methods Med Res 2012
6
Doubly robust nonparametric inference on the average treatment effect.
D Benkeser, M Carone, M J Van Der Laan, P B Gilbert. Biometrika 2017
D Benkeser, M Carone, M J Van Der Laan, P B Gilbert. Biometrika 2017
15
Recursive partitioning for heterogeneous causal effects.
Susan Athey, Guido Imbens. Proc Natl Acad Sci U S A 2016
Susan Athey, Guido Imbens. Proc Natl Acad Sci U S A 2016
5
Matching methods for causal inference: A review and a look forward.
Elizabeth A Stuart. Stat Sci 2010
Elizabeth A Stuart. Stat Sci 2010
5
Cohort Profile: The Health Outcomes and Measures of the Environment (HOME) study.
Joseph M Braun, Geetika Kalloo, Aimin Chen, Kim N Dietrich, Stacey Liddy-Hicks, Samantha Morgan, Yingying Xu, Kimberly Yolton, Bruce P Lanphear. Int J Epidemiol 2017
Joseph M Braun, Geetika Kalloo, Aimin Chen, Kim N Dietrich, Stacey Liddy-Hicks, Samantha Morgan, Yingying Xu, Kimberly Yolton, Bruce P Lanphear. Int J Epidemiol 2017
5
Constructing inverse probability weights for marginal structural models.
Stephen R Cole, Miguel A Hernán. Am J Epidemiol 2008
Stephen R Cole, Miguel A Hernán. Am J Epidemiol 2008
5
An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.
Peter C Austin. Multivariate Behav Res 2011
Peter C Austin. Multivariate Behav Res 2011
5
Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.
M A Hernán, B Brumback, J M Robins. Epidemiology 2000
M A Hernán, B Brumback, J M Robins. Epidemiology 2000
5
Super-Learning of an Optimal Dynamic Treatment Rule.
Alexander R Luedtke, Mark J van der Laan. Int J Biostat 2016
Alexander R Luedtke, Mark J van der Laan. Int J Biostat 2016
20
Improving propensity score weighting using machine learning.
Brian K Lee, Justin Lessler, Elizabeth A Stuart. Stat Med 2010
Brian K Lee, Justin Lessler, Elizabeth A Stuart. Stat Med 2010
5
Implementation of G-computation on a simulated data set: demonstration of a causal inference technique.
Jonathan M Snowden, Sherri Rose, Kathleen M Mortimer. Am J Epidemiol 2011
Jonathan M Snowden, Sherri Rose, Kathleen M Mortimer. Am J Epidemiol 2011
5
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models.
Evangelia Christodoulou, Jie Ma, Gary S Collins, Ewout W Steyerberg, Jan Y Verbakel, Ben Van Calster. J Clin Epidemiol 2019
Evangelia Christodoulou, Jie Ma, Gary S Collins, Ewout W Steyerberg, Jan Y Verbakel, Ben Van Calster. J Clin Epidemiol 2019
5
What is Machine Learning? A Primer for the Epidemiologist.
Qifang Bi, Katherine E Goodman, Joshua Kaminsky, Justin Lessler. Am J Epidemiol 2019
Qifang Bi, Katherine E Goodman, Joshua Kaminsky, Justin Lessler. Am J Epidemiol 2019
6
Machine Learning for Causal Inference: On the Use of Cross-fit Estimators.
Paul N Zivich, Alexander Breskin. Epidemiology 2021
Paul N Zivich, Alexander Breskin. Epidemiology 2021
35
Targeted estimation of nuisance parameters to obtain valid statistical inference.
Mark J van der Laan. Int J Biostat 2014
Mark J van der Laan. Int J Biostat 2014
12
Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.
Romain Pirracchio, Maya L Petersen, Marco Carone, Matthieu Resche Rigon, Sylvie Chevret, Mark J van der Laan. Lancet Respir Med 2015
Romain Pirracchio, Maya L Petersen, Marco Carone, Matthieu Resche Rigon, Sylvie Chevret, Mark J van der Laan. Lancet Respir Med 2015
4
Propensity score estimation with boosted regression for evaluating causal effects in observational studies.
Daniel F McCaffrey, Greg Ridgeway, Andrew R Morral. Psychol Methods 2004
Daniel F McCaffrey, Greg Ridgeway, Andrew R Morral. Psychol Methods 2004
4
Environmental chemicals in pregnant women in the United States: NHANES 2003-2004.
Tracey J Woodruff, Ami R Zota, Jackie M Schwartz. Environ Health Perspect 2011
Tracey J Woodruff, Ami R Zota, Jackie M Schwartz. Environ Health Perspect 2011
4
Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available.
Miguel A Hernán, James M Robins. Am J Epidemiol 2016
Miguel A Hernán, James M Robins. Am J Epidemiol 2016
4
Sensitivity Analysis in Observational Research: Introducing the E-Value.
Tyler J VanderWeele, Peng Ding. Ann Intern Med 2017
Tyler J VanderWeele, Peng Ding. Ann Intern Med 2017
4
Using Super Learner Prediction Modeling to Improve High-dimensional Propensity Score Estimation.
Richard Wyss, Sebastian Schneeweiss, Mark van der Laan, Samuel D Lendle, Cheng Ju, Jessica M Franklin. Epidemiology 2018
Richard Wyss, Sebastian Schneeweiss, Mark van der Laan, Samuel D Lendle, Cheng Ju, Jessica M Franklin. Epidemiology 2018
12
Machine learning in the estimation of causal effects: targeted minimum loss-based estimation and double/debiased machine learning.
Iván Díaz. Biostatistics 2020
Iván Díaz. Biostatistics 2020
30
You are smarter than you think: (super) machine learning in context.
Alexander P Keil, Jessie K Edwards. Eur J Epidemiol 2018
Alexander P Keil, Jessie K Edwards. Eur J Epidemiol 2018
50
Marginal structural models and causal inference in epidemiology.
J M Robins, M A Hernán, B Brumback. Epidemiology 2000
J M Robins, M A Hernán, B Brumback. Epidemiology 2000
4
4
Mortality risk score prediction in an elderly population using machine learning.
Sherri Rose. Am J Epidemiol 2013
Sherri Rose. Am J Epidemiol 2013
5
Targeted maximum likelihood estimation for a binary treatment: A tutorial.
Miguel Angel Luque-Fernandez, Michael Schomaker, Bernard Rachet, Mireille E Schnitzer. Stat Med 2018
Miguel Angel Luque-Fernandez, Michael Schomaker, Bernard Rachet, Mireille E Schnitzer. Stat Med 2018
13
The Highly Adaptive Lasso Estimator.
David Benkeser, Mark van der Laan. Proc Int Conf Data Sci Adv Anal 2016
David Benkeser, Mark van der Laan. Proc Int Conf Data Sci Adv Anal 2016
16
Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study.
Jared K Lunceford, Marie Davidian. Stat Med 2004
Jared K Lunceford, Marie Davidian. Stat Med 2004
3
Optimal serum cotinine levels for distinguishing cigarette smokers and nonsmokers within different racial/ethnic groups in the United States between 1999 and 2004.
Neal L Benowitz, John T Bernert, Ralph S Caraballo, David B Holiday, Jiantong Wang. Am J Epidemiol 2009
Neal L Benowitz, John T Bernert, Ralph S Caraballo, David B Holiday, Jiantong Wang. Am J Epidemiol 2009
3
Dose-response analyses using restricted cubic spline functions in public health research.
Loic Desquilbet, François Mariotti. Stat Med 2010
Loic Desquilbet, François Mariotti. Stat Med 2010
3
Phenotypic dichotomy following developmental exposure to perfluorooctanoic acid (PFOA) in female CD-1 mice: Low doses induce elevated serum leptin and insulin, and overweight in mid-life.
Erin P Hines, Sally S White, Jason P Stanko, Eugene A Gibbs-Flournoy, Christopher Lau, Suzanne E Fenton. Mol Cell Endocrinol 2009
Erin P Hines, Sally S White, Jason P Stanko, Eugene A Gibbs-Flournoy, Christopher Lau, Suzanne E Fenton. Mol Cell Endocrinol 2009
3
Improved selectivity for the analysis of maternal serum and cord serum for polyfluoroalkyl chemicals.
Kayoko Kato, Brian J Basden, Larry L Needham, Antonia M Calafat. J Chromatogr A 2011
Kayoko Kato, Brian J Basden, Larry L Needham, Antonia M Calafat. J Chromatogr A 2011
3
Prenatal perfluoroalkyl substance exposure and child adiposity at 8 years of age: The HOME study.
Joseph M Braun, Aimin Chen, Megan E Romano, Antonia M Calafat, Glenys M Webster, Kimberly Yolton, Bruce P Lanphear. Obesity (Silver Spring) 2016
Joseph M Braun, Aimin Chen, Megan E Romano, Antonia M Calafat, Glenys M Webster, Kimberly Yolton, Bruce P Lanphear. Obesity (Silver Spring) 2016
3
Prenatal exposure to perfluorooctanoate and risk of overweight at 20 years of age: a prospective cohort study.
Thorhallur I Halldorsson, Dorte Rytter, Line Småstuen Haug, Bodil Hammer Bech, Inge Danielsen, Georg Becher, Tine Brink Henriksen, Sjurdur F Olsen. Environ Health Perspect 2012
Thorhallur I Halldorsson, Dorte Rytter, Line Småstuen Haug, Bodil Hammer Bech, Inge Danielsen, Georg Becher, Tine Brink Henriksen, Sjurdur F Olsen. Environ Health Perspect 2012
3
Improving propensity score estimators' robustness to model misspecification using super learner.
Romain Pirracchio, Maya L Petersen, Mark van der Laan. Am J Epidemiol 2015
Romain Pirracchio, Maya L Petersen, Mark van der Laan. Am J Epidemiol 2015
4
A structural approach to selection bias.
Miguel A Hernán, Sonia Hernández-Díaz, James M Robins. Epidemiology 2004
Miguel A Hernán, Sonia Hernández-Díaz, James M Robins. Epidemiology 2004
3
An increase in the incidence of gestational diabetes mellitus: Northern California, 1991-2000.
Assiamira Ferrara, Henry S Kahn, Charles P Quesenberry, Candice Riley, Monique M Hedderson. Obstet Gynecol 2004
Assiamira Ferrara, Henry S Kahn, Charles P Quesenberry, Candice Riley, Monique M Hedderson. Obstet Gynecol 2004
3
Challenges in Obtaining Valid Causal Effect Estimates with Machine Learning Algorithms.
Ashley I Naimi, Alan E Mishler, Edward H Kennedy. Am J Epidemiol 2021
Ashley I Naimi, Alan E Mishler, Edward H Kennedy. Am J Epidemiol 2021
37
The parametric g-formula for time-to-event data: intuition and a worked example.
Alexander P Keil, Jessie K Edwards, David B Richardson, Ashley I Naimi, Stephen R Cole. Epidemiology 2014
Alexander P Keil, Jessie K Edwards, David B Richardson, Ashley I Naimi, Stephen R Cole. Epidemiology 2014
3
Variable selection for propensity score models.
M Alan Brookhart, Sebastian Schneeweiss, Kenneth J Rothman, Robert J Glynn, Jerry Avorn, Til Stürmer. Am J Epidemiol 2006
M Alan Brookhart, Sebastian Schneeweiss, Kenneth J Rothman, Robert J Glynn, Jerry Avorn, Til Stürmer. Am J Epidemiol 2006
3
Does obesity shorten life? The importance of well-defined interventions to answer causal questions.
M A Hernán, S L Taubman. Int J Obes (Lond) 2008
M A Hernán, S L Taubman. Int J Obes (Lond) 2008
3
Targeted maximum likelihood estimation in safety analysis.
Samuel D Lendle, Bruce Fireman, Mark J van der Laan. J Clin Epidemiol 2013
Samuel D Lendle, Bruce Fireman, Mark J van der Laan. J Clin Epidemiol 2013
21
Effect decomposition in the presence of an exposure-induced mediator-outcome confounder.
Tyler J Vanderweele, Stijn Vansteelandt, James M Robins. Epidemiology 2014
Tyler J Vanderweele, Stijn Vansteelandt, James M Robins. Epidemiology 2014
3
The potential of predictive analytics to provide clinical decision support in depression treatment planning.
Ronald C Kessler. Curr Opin Psychiatry 2018
Ronald C Kessler. Curr Opin Psychiatry 2018
6
Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.