James M. W. Robins
Impact in
- Statistics and Probability top 0.01%
- Advanced Causal Inference Techniques
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Statistical Methods in Clinical Trials
- Modeling and Simulation top 0.1%
- COVID-19 epidemiological studies
Papers in
-
- Advanced Causal Inference Techniques 170
- Statistical Methods and Inference 141
- Statistical Methods and Bayesian Inference 124
- Statistical Methods in Clinical Trials 55
-
- Health Systems, Economic Evaluations, Quality of Life 37
- Co-authors
- Miguel Ángel Hernán (57 shared papers)Sander Greenland (20 shared papers)Andrea G. Rotnitzky (37 shared papers)Babette Brumback (5 shared papers)Judea Pearl (2 shared papers)Lue Ping Zhao (4 shared papers)Sonia Hernández–Dı́az (3 shared papers)Sander Greenland (5 shared papers)
- Journals
- Journal of the American Statistical Association (47 papers)Epidemiology (27 papers)American Journal of Epidemiology (27 papers)Biometrika (21 papers)Statistics in Medicine (20 papers)
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
James M. W. Robins
324 papers receiving 51.5k citations
James M. W. Robins's Hit Papers
Peers
Comparison fields: 5 of 226
- Statistics and Probability 24.5k
- Modeling and Simulation 1.6k
- Economics and Econometrics 8.1k
- Health 1.4k
- Infectious Diseases 2.6k
Countries citing papers authored by James M. W. Robins
This map shows the geographic impact of James M. W. Robins's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by James M. W. Robins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James M. W. Robins more than expected).
Fields of papers citing papers by James M. W. Robins
This network shows the impact of papers produced by James M. W. Robins. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by James M. W. Robins. The network helps show where James M. W. Robins may publish in the future.
Co-authors
The 25 scholars most cited alongside James M. W. Robins, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 332 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Marginal Structural Models and Causal Inference in Epidemiology Hit paper breakdown → | 2000 | 4291 |
| 2 | Causal Diagrams for Epidemiologic Research Hit paper breakdown → | 1999 | 2950 |
| 3 | A Structural Approach to Selection Bias Hit paper breakdown → | 2004 | 2095 |
| 4 | Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available: Table 1. Hit paper breakdown → | 2016 | 1941 |
| 5 | Estimation of Regression Coefficients When Some Regressors are not Always Observed Hit paper breakdown → | 1994 | 1857 |
| 6 | A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect Hit paper breakdown → | 1986 | 1651 |
| 7 | Double/debiased machine learning for treatment and structural parameters Hit paper breakdown → | 2017 | 1474 |
| 8 | Marginal Structural Models to Estimate the Causal Effect of Zidovudine on the Survival of HIV-Positive Men Hit paper breakdown → | 2000 | 1457 |
| 9 | Identifiability and Exchangeability for Direct and Indirect Effects Hit paper breakdown → | 1992 | 1370 |
| 10 | Doubly Robust Estimation in Missing Data and Causal Inference Models Hit paper breakdown → | 2005 | 1282 |
| 11 | Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data Hit paper breakdown → | 1995 | 1137 |
| 12 | Transmission Dynamics and Control of Severe Acute Respiratory Syndrome Hit paper breakdown → | 2003 | 1118 |
| 13 | Methotrexate and mortality in patients with rheumatoid arthritis: a prospective study Hit paper breakdown → | 2002 | 939 |
| 14 | 1999 | 728 | |
| 15 | Instruments for Causal Inference Hit paper breakdown → | 2006 | 720 |
| 16 | Unified Methods for Censored Longitudinal Data and Causality Hit paper breakdown → | 2003 | 683 |
| 17 | 1985 | 678 | |
| 18 | 2000 | 666 | |
| 19 | 1999 | 655 | |
| 20 | Observational Studies Analyzed Like Randomized Experiments Hit paper breakdown → | 2008 | 654 |
About James M. W. Robins
James M. W. Robins is a scholar working on Statistics and Probability, Economics and Econometrics, Artificial Intelligence, Infectious Diseases and Modeling and Simulation, having authored 332 papers that have together received 53.8k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (170 papers), Statistical Methods and Inference (141 papers), Statistical Methods and Bayesian Inference (124 papers), Statistical Methods in Clinical Trials (55 papers), Health Systems, Economic Evaluations, Quality of Life (37 papers), Bayesian Modeling and Causal Inference (17 papers), Bayesian Methods and Mixture Models (16 papers) and HIV/AIDS drug development and treatment (12 papers). The work is most often cited by research in Statistics and Probability (24.5k citations), Modeling and Simulation (1.6k citations), Economics and Econometrics (8.1k citations), Health (1.4k citations) and Infectious Diseases (2.6k citations). James M. W. Robins has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Miguel Ángel Hernán, Sander Greenland, Andrea G. Rotnitzky, Babette Brumback, Judea Pearl, Lue Ping Zhao, Sonia Hernández–Dı́az, Sander Greenland, Heejung Bang and Daniel O. Scharfstein. Their work appears in journals such as Journal of the American Statistical Association, Epidemiology, American Journal of Epidemiology, Biometrika and Statistics in Medicine.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.