James M. Robins

James M. Robins

Harvard University

H-index: 131

North America-United States

About James M. Robins

James M. Robins, With an exceptional h-index of 131 and a recent h-index of 83 (since 2020), a distinguished researcher at Harvard University, specializes in the field of statistics, epidemiology, biostatistics, causal inference.

His recent articles reflect a diverse array of research interests and contributions to the field:

Grace periods in comparative effectiveness studies of sustained treatments

Marshall Joffe’s Contributions to Causal Inference, Biostatistics, and Epidemiology

Comparison of the test-negative design and cohort design with explicit target trial emulation for evaluating COVID-19 vaccine effectiveness

Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators

Thomas S. Richardson and James M. Robins’ contribution to the Discussion of ‘Parameterizing and Simulating from Causal Models’ by Evans and Didelez’

Assumptions and bounds in the instrumental variable model

Rejoinder: A formal causal interpretation of the case‐crossover design

A formal causal interpretation of the case‐crossover design

James M. Robins Information

University

Position

professor of epidemiology and biostatistics of public health

Citations(all)

97577

Citations(since 2020)

40839

Cited By

72951

hIndex(all)

131

hIndex(since 2020)

83

i10Index(all)

343

i10Index(since 2020)

268

Email

University Profile Page

Harvard University

Google Scholar

View Google Scholar Profile

James M. Robins Skills & Research Interests

statistics

epidemiology

biostatistics

causal inference

Top articles of James M. Robins

Title

Journal

Author(s)

Publication Date

Grace periods in comparative effectiveness studies of sustained treatments

Journal of the Royal Statistical Society Series A: Statistics in Society

Kerollos Nashat Wanis

Aaron L Sarvet

Lan Wen

Jason P Block

Sheryl L Rifas-Shiman

...

2024/1/22

Marshall Joffe’s Contributions to Causal Inference, Biostatistics, and Epidemiology

American Journal of Epidemiology

Dane Isenberg

Edward H Kennedy

J Richard Landis

Nandita Mitra

James M Robins

...

2024/4

Comparison of the test-negative design and cohort design with explicit target trial emulation for evaluating COVID-19 vaccine effectiveness

Epidemiology

Guilin Li

Hanna Gerlovin

Michael J Figueroa Muñiz

Jessica K Wise

Arin L Madenci

...

2024/3/1

Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators

Journal of Econometrics

Lin Liu

Rajarshi Mukherjee

James M Robins

2024/3/1

Thomas S. Richardson and James M. Robins’ contribution to the Discussion of ‘Parameterizing and Simulating from Causal Models’ by Evans and Didelez’

Journal of the Royal Statistical Society Series B: Statistical Methodology

TS Richardson

JM Robins

2024/2/23

Assumptions and bounds in the instrumental variable model

arXiv preprint arXiv:2401.13758

Thomas S Richardson

James M Robins

2024/1/24

Rejoinder: A formal causal interpretation of the case‐crossover design

Biometrics

Zach Shahn

Miguel A Hernán

James M Robins

2023/6

A formal causal interpretation of the case‐crossover design

Biometrics

Zach Shahn

Miguel A Hernán

James M Robins

2023/6

Potential outcome and decision theoretic foundations for statistical causality

Journal of Causal Inference

Thomas S Richardson

James M Robins

2023/10/25

THE ANNALS

The Annals of Probability

PETER K FRIZ

PAVEL ZORIN-KRANICH

XIN CHEN

XUEMEI LI

BO WU

...

2023/3

Conditional separable effects

Journal of the American Statistical Association

Mats J Stensrud

James M Robins

Aaron Sarvet

Eric J Tchetgen Tchetgen

Jessica G Young

2023/10/2

Nested Markov properties for acyclic directed mixed graphs

The Annals of Statistics

Thomas S Richardson

Robin J Evans

James M Robins

Ilya Shpitser

2023/2

Can we falsify the justification of the validity of Wald confidence intervals of doubly robust functionals, without assumptions?

arXiv preprint arXiv:2306.10590

Lin Liu

Rajarshi Mukherjee

James M Robins

2023/6/18

Sensitivity analysis using bias functions for studies extending inferences from a randomized trial to a target population

Statistics in Medicine

Issa J Dahabreh

James M Robins

Sebastien J‐PA Haneuse

Iman Saeed

Sarah E Robertson

...

2023/6/15

Multivariate counterfactual systems and causal graphical models

Ilya Shpitser

Thomas S Richardson

James M Robins

2022/2/28

Jiwei Zhao’s contribution to the Discussion of ‘Assumption-lean inference for generalised linear model parameters’ by Vansteelandt and Dukes

L Liu

R Mukherjee

JM Robins

EJ Tchetgen Tchetgen

WK Newey

2022/7/1

Deep learning methods for proximal inference via maximum moment restriction

Advances in Neural Information Processing Systems

Benjamin Kompa

David Bellamy

Tom Kolokotrones

James Robins

Andrew Beam

2022/12/6

An interventionist approach to mediation analysis

James M Robins

Thomas S Richardson

Ilya Shpitser

2022/2/28

Locally robust semiparametric estimation

Econometrica 2022; arXiv preprint arXiv:1608.00033

Victor Chernozhukov

Juan Carlos Escanciano

Hidehiko Ichimura

Whitney K Newey

James M Robins

2022

Causal and counterfactual views of missing data models

arXiv preprint arXiv:2210.05558

Razieh Nabi

Rohit Bhattacharya

Ilya Shpitser

James Robins

2022/10/11

See List of Professors in James M. Robins University(Harvard University)

Co-Authors

H-index: 152
Sander Greenland

Sander Greenland

University of California, Los Angeles

H-index: 128
Marc Lipsitch

Marc Lipsitch

Harvard University

H-index: 127
Miguel Hernan

Miguel Hernan

Harvard University

H-index: 120
Judea Pearl

Judea Pearl

University of California, Los Angeles

H-index: 106
Tyler J. VanderWeele

Tyler J. VanderWeele

Harvard University

H-index: 90
Mark van der Laan

Mark van der Laan

University of California, Berkeley

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