The Division of Biostatistics is one of five divisions of the School of Public Health at the University of California, Berkeley. Its mission is the promotion of teaching and research of biostatistical methods by faculty and graduate students. Graduate students are admitted to M.A. and Ph.D. programs through the Group in Biostatistics which is a joint program of the School of Public Health and the Department of Statistics.
The Biostatistics Working Paper series includes articles on statistical methods and applications developed by faculty and visitors of the Division of Biostatistics. In general, articles dated 2001 and later are downloadable from this site. For earlier articles that have appeared in print, we have included an abstract with a citation. Articles that are not downloadable or are unavailable in print may be requested from
Nicholas P. Jewell
Chair, Group in Biostatistics
University of California, Berkeley
140 Warren Hall
Berkeley, CA 94720-7360
Papers from 2017
Evaluation of Progress Towards the UNAIDS 90-90-90 HIV Care Cascade: A Description of Statistical Methods Used in an Interim Analysis of the Intervention Communities in the SEARCH Study, Laura Balzer, Joshua Schwab, Mark J. van der Laan, and Maya L. Petersen
Papers from 2016
Doubly-robust Nonparametric Inference on the Average Treatment Effect, David Benkeser, Marco Carone, Mark J. van der Laan, and Peter Gilbert
Online Cross-Validation-Based Ensemble Learning, David Benkeser, Samuel D. Lendle, Cheng Ju, and Mark J. van der Laan
Practical Targeted Learning from Large Data Sets by Survey Sampling, Patrice Bertail, Antoine Chambaz, and Emilien Joly
Data-adaptive Inference of the Optimal Treatment Rule and its Mean Reward. The Masked Bandit, Antoine Chambaz, Wenjing Zheng, and Mark J. van der Laan
Propensity score prediction for electronic healthcare databases using Super Learner and High-dimensional Propensity Score Methods, Cheng Ju, Mary Combs, Samuel D. Lendle, Jessica M. Franklin, Richard Wyss, Sebastian Schneeweiss, and Mark J. van der Laan
Scalable Collaborative Targeted Learning for High-dimensional Data, Cheng Ju, Susan Gruber, Samuel D. Lendle, Antoine Chambaz, Jessica M. Franklin, Richard Wyss, Sebastian Schneeweiss, and Mark J. van der Laan
Evaluating the Impact of Treating the Optimal Subgroup, Alexander R. Luedtke and Mark J. van der Laan
TMLE for Marginal Structural Models Based on an Instrument, Boriska Toth and Mark J. van der Laan
Evaluating the Impact of a HIV Low-Risk Express Care Task-Shifting Program: A Case Study of the Targeted Learning Roadmap, Linh Tran, Constantin T. Yiannoutsos, Beverly S. Musick, Kara K. Wools-Kaloustian, Abraham Siika, Sylvester Kimaiyo, Mark J. van der Laan, and Maya L. Petersen
One-Step Targeted Minimum Loss-based Estimation Based on Universal Least Favorable One-Dimensional Submodels, Mark J. van der Laan and Susan Gruber
Performance-constrained Binary Classification Using Ensemble Learning: an Application to Cost-efficient Targeted PrEP Strategies, Wenjing Zheng, Laura Balzer, Maya L. Petersen, and Mark J. van der Laan
Marginal Structural Models with Counterfactual Effect Modifiers, Wenjing Zheng, Zhehui Luo, and Mark J. van der Laan
Papers from 2015
Targeted Estimation and Inference for the Sample Average Treatment Effect, Laura B. Balzer, Maya L. Petersen, and Mark J. van der Laan
Adaptive Pre-specification in Randomized Trials With and Without Pair-Matching, Laura B. Balzer, Mark J. van der Laan, and Maya L. Petersen
Second Order Inference for the Mean of a Variable Missing at Random, Ivan Diaz, Marco Carone, and Mark J. van der Laan
An Omnibus Nonparametric Test of Equality in Distribution for Unknown Functions, Alexander R. Luedtke, Marco Carone, and Mark J. van der Laan
The Statistics of Sensitivity Analyses, Alexander R. Luedtke, Ivan Diaz, and Mark J. van der Laan
Optimal Dynamic Treatments in Resource-Limited Settings, Alexander R. Luedtke and Mark J. van der Laan
Double Robust Estimation of Encouragement-design Intervention Effects Transported Across Sites, Kara E. Rudolph and Mark J. van der Laan
Semi-Parametric Estimation and Inference for the Mean Outcome of the Single Time-Point Intervention in a Causally Connected Population, Oleg Sofrygin and Mark J. van der Laan
A Generally Efficient Targeted Minimum Loss Based Estimator, Mark J. van der Laan
One-Step Targeted Minimum Loss-based Estimation Based on Universal Least Favorable One-Dimensional Submodels, Mark J. van der Laan
Computerizing Efficient Estimation of a Pathwise Differentiable Target Parameter, Mark J. van der Laan, Marco Carone, and Alexander R. Luedtke
Drawing Valid Targeted Inference When Covariate-adjusted Response-adaptive RCT Meets Data-adaptive Loss-based Estimation, With An Application To The LASSO, Wenjing Zheng, Antoine Chambaz, and Mark J. van der Laan
Papers from 2014
Adaptive Pair-Matching in the SEARCH Trial and Estimation of the Intervention Effect, Laura Balzer, Maya L. Petersen, and Mark J. van der Laan
Higher-order Targeted Minimum Loss-based Estimation, Marco Carone, Iván Díaz, and Mark J. van der Laan
Targeted Covariate-Adjusted Response-Adaptive LASSO-Based Randomized Controlled Trials, Antoine Chambaz, Wenjing Zheng, and Mark J. van der Laan
Sieve Plateau Variance Estimators: A New Approach to Confidence Interval Estimation for Dependent Data, Molly M. Davies and Mark J. van der Laan
Deductive Derivation and Computerization of Compatible Semiparametric Efficient Estimation, Constantine E. Frangakis, Tianchen Qian, Zhenke Wu, and Ivan Diaz
Statistical Inference for the Mean Outcome Under a Possibly Non-Unique Optimal Treatment Strategy, Alexander R. Luedtke and Mark J. van der Laan
Super-Learning of an Optimal Dynamic Treatment Rule, Alexander R. Luedtke and Mark J. van der Laan
A Scalable Supervised Subsemble Prediction Algorithm, Stephanie Sapp and Mark J. van der Laan
Online Targeted Learning, Mark J. van der Laan and Samuel D. Lendle
Targeted Learning of an Optimal Dynamic Treatment, and Statistical Inference for its Mean Outcome, Mark J. van der Laan and Alexander R. Luedtke
Targeted Learning of the Mean Outcome Under an Optimal Dynamic Treatment Rule, Mark J. van der Laan and Alexander R. Luedtke
Entering the Era of Data Science: Targeted Learning and the Integration of Statistics and Computational Data Analysis, Mark J. van der Laan and Richard J.C.M. Starmans
A Novel Targeted Learning Method for Quantitative Trait Loci Mapping, Hui Wang, Zhongyang Zhang, Sherri Rose, and Mark J. van der Laan
Papers from 2013
Estimating Effects on Rare Outcomes: Knowledge is Power, Laura B. Balzer and Mark J. van der Laan
Variable Importance and Prediction Methods for Longitudinal Problems with Missing Variables, Ivan Diaz, Alan E. Hubbard, Anna Decker, and Mitchell Cohen
Targeted Data Adaptive Estimation of the Causal Dose Response Curve, Iván Díaz and Mark J. van der Laan
An Application Of Machine Learning Methods To The Derivation Of Exposure-Response Curves For Respiratory Outcomes, Ekaterina Eliseeva, Alan E. Hubbard, and Ira B. Tager
Testing the Relative Performance of Data Adaptive Prediction Algorithms: A Generalized Test of Conditional Risk Differences, Benjamin A. Goldstein, Eric Polley, Farren Briggs, and Mark J. van der Laan
Vertically Shifted Mixture Models for Clustering Longitudinal Data by Shape, Brianna C. Heggeseth and Nicholas P. Jewell
Adapting Data Adaptive Methods for Small, but High Dimensional Omic Data: Applications to GWAS/EWAS and More, Sara Kherad Pajouh, Alan E. Hubbard, and Martyn T. Smith
Balancing Score Adjusted Targeted Minimum Loss-based Estimation, Samuel D. Lendle, Bruce Fireman, and Mark J. van der Laan
Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models, Maya L. Petersen, Joshua Schwab, Susan Gruber, Nello Blaser, Michael Schomaker, and Mark J. van der Laan
Subsemble: An Ensemble Method for Combining Subset-Specific Algorithm Fits, Stephanie Sapp, Mark J. van der Laan, and John Canny
Targeted Estimation of Variable Importance Measures with Interval-Censored Outcomes, Stephanie Sapp, Mark J. van der Laan, and Kimberly Page
Targeted Learning of an Optimal Dynamic Treatment, and Statistical Inference for its Mean Outcome, Mark J. van der Laan
Statistical Inference for Data Adaptive Target Parameters, Mark J. van der Laan, Alan E. Hubbard, and Sara Kherad Pajouh
Challenges in Estimating the Causal Effect of an Intervention with Pre-Post Data (Part 1): Definition & Identification of the Causal Parameter, Ann M. Weber, Mark J. van der Laan, and Maya L. Petersen
Papers from 2012
Targeted Learning of The Probability of Success of An In Vitro Fertilization Program Controlling for Time-dependent Confounders, Antoine Chambaz, Sherri Rose, Jean Bouyer, and Mark J. van der Laan
Avoiding Boundary Estimates in Linear Mixed Models Through Weakly Informative Priors, Yeojin Chung, Sophia Rabe-Hesketh, Andrew Gelman, Jingchen Liu, and Vincent Dorie
Optimal Spatial Prediction Using Ensemble Machine Learning, Molly M. Davies and Mark J. van der Laan
Assessing the Causal Effect of Policies: An Approach Based on Stochastic Interventions, Iván Díaz and Mark J. van der Laan
Sensitivity Analysis for Causal Inference Under Unmeasured Confounding and Measurement Error Problems, Iván Díaz and Mark J. van der Laan
The Impact of Covariance Misspecification in Multivariate Gaussian Mixtures on Estimation and Inference: An Application to Longitudinal Modeling, Brianna C. Heggeseth and Nicholas P. Jewell
Computationally Efficient Confidence Intervals for Cross-validated Area Under the ROC Curve Estimates, Erin LeDell, Maya L. Petersen, and Mark J. van der Laan
Targeted Learning for Causality and Statistical Analysis in Medical Research, Sherri Rose, Richard J.C.M. Starmans, and Mark J. van der Laan
Causal Inference for Networks, Mark J. van der Laan
Statistical Inference when using Data Adaptive Estimators of Nuisance Parameters, Mark J. van der Laan
Adaptive Matching in Randomized Trials and Observational Studies, Mark J. van der Laan, Laura Balzer, and Maya L. Petersen
Causal Mediation in a Survival Setting with Time-Dependent Mediators, Wenjing Zheng and Mark J. van der Laan
Papers from 2011
Estimation of a Non-Parametric Variable Importance Measure of a Continuous Exposure, Chambaz Antoine, Pierre Neuvial, and Mark J. van der Laan
Targeted Maximum Likelihood Estimation for Dynamic Treatment Regimes in Sequential Randomized Controlled Trials, Paul Chaffee and Mark J. van der Laan
Targeted Minimum Loss Based Estimation Based on Directly Solving the Efficient Influence Curve Equation, Paul Chaffee and Mark J. van der Laan
Threshold Regression Models Adapted to Case-Control Studies, and the Risk of Lung Cancer Due to Occupational Exposure to Asbestos in France, Antoine Chambaz, Dominique Choudat, Catherine Huber, Jean-Claude Pairon, and Mark J. van der Laan
Estimation and Testing in Targeted Group Sequential Covariate-adjusted Randomized Clinical Trials, Antoine Chambaz and Mark J. van der Laan
Population Intervention Causal Effects Based on Stochastic Interventions, Ivan Diaz Munoz and Mark J. van der Laan
Super Learner Based Conditional Density Estimation with Application to Marginal Structural Models, Ivan Diaz Munoz and Mark J. van der Laan
A Generalized Approach for Testing the Association of a Set of Predictors with an Outcome: A Gene Based Test, Benjamin A. Goldstein, Alan E. Hubbard, and Lisa F. Barcellos
Targeted Minimum Loss Based Estimator that Outperforms a given Estimator, Susan Gruber and Mark J. van der Laan
tmle: An R Package for Targeted Maximum Likelihood Estimation, Susan Gruber and Mark J. van der Laan
Identification and Efficient Estimation of the Natural Direct Effect Among the Untreated, Samuel D. Lendle and Mark J. van der Laan
The Relative Performance of Targeted Maximum Likelihood Estimators, Kristin E. Porter, Susan Gruber, Mark J. van der Laan, and Jasjeet S. Sekhon
GC-Content Normalization for RNA-Seq Data, Davide Risso, Katja Schwartz, Gavin Sherlock, and Sandrine Dudoit
Variable Importance Analysis with the multiPIM R Package, Stephan J. Ritter, Nicholas P. Jewell, and Alan E. Hubbard
A General Implementation of TMLE for Longitudinal Data Applied to Causal Inference in Survival Analysis, Ori M. Stitelman, Victor De Gruttola, and Mark J. van der Laan
Targeted Maximum Likelihood Estimation of Conditional Relative Risk in a Semi-parametric Regression Model, Cathy Tuglus, Kristin E. Porter, and Mark J. van der Laan
Targeted Minimum Loss Based Estimation of an Intervention Specific Mean Outcome, Mark J. van der Laan and Susan Gruber
Targeted Methods for Finding Quantitative Trait Loci, Hui Wang, Sherri Rose, and Mark J. van der Laan
Targeted Maximum Likelihood Estimation of Natural Direct Effect, Wenjing Zheng and Mark J. van der Laan
Papers from 2010
Permutation-based Pathway Testing using the Super Learner Algorithm, Paul Chaffee, Alan E. Hubbard, and Mark L. van der Laan
Targeting The Optimal Design In Randomized Clinical Trials With Binary Outcomes And No Covariate, Antoine Chambaz and Mark J. van der Laan
Targeted Bayesian Learning, Ivan Diaz Munoz, Alan E. Hubbard, and Mark J. van der Laan
A Targeted Maximum Likelihood Estimator of a Causal Effect on a Bounded Continuous Outcome, Susan Gruber and Mark J. van der Laan
Gains in Power from Structured Two-Sample Tests of Means on Graphs, Laurent Jacob, Pierre Neuvial, and Sandrine Dudoit
Observational Study and Individualized Antiretroviral Therapy Initiation Rules for Reducing Cancer Incidence in HIV-Infected Patients, Romain Neugebauer, Michael J. Silverberg, and Mark J. van der Laan
Diagnosing and Responding to Violations in the Positivity Assumption, Maya L. Petersen, Kristin Porter, Susan Gruber, Yue Wang, and Mark J. van der Laan
Super Learner In Prediction, Eric C. Polley and Mark J. van der Laan
Optimizing Randomized Trial Designs to Distinguish which Subpopulations Benefit from Treatment, Michael Rosenblum and Mark J. van der Laan
Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables, Michael Rosenblum and Mark J. van der Laan
Simple Examples of Estimating Causal Effects Using Targeted Maximum Likelihood Estimation, Michael Rosenblum and Mark J. van der Laan
Targeted Maximum Likelihood Estimation of the Parameter of a Marginal Structural Model, Michael Rosenblum and Mark J. van der Laan
The Impact Of Coarsening The Explanatory Variable Of Interest In Making Causal Inferences: Implicit Assumptions Behind Dichotomizing Variables, Ori M. Stitelman, Alan E. Hubbard, and Nicholas P. Jewell
Collaborative Targeted Maximum Likelihood For Time To Event Data, Ori M. Stitelman and Mark J. van der Laan
Targeted Maximum Likelihood Method for Repeated Measures Semiparametric Regression: Discovery for Transcription Factor Activity, Catherine Tuglus and Mark J. van der Laan
Estimation of Causal Effects of Community Based Interventions, Mark J. van der Laan
Targeted Maximum Likelihood Based Causal Inference, Mark J. van der Laan