Mark J. van der Laan
- Statistics and Probability top 0.01%
- Economics and Econometrics top 0.5%
- Artificial Intelligence top 1%
- Molecular Biology top 10%
- Epidemiology top 5%
- Co-authors
- Sandrine DudoitAlan HubbardSusan GruberEric C. PolleySherri RoseMaya L. PetersenDaniel B. RubinKatherine S. Pollard
- Topics
- Statistical Methods and Inference (193 papers)Advanced Causal Inference Techniques (165 papers)Statistical Methods and Bayesian Inference (143 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationBioinformatics
- Partner nations
- United StatesFranceDenmark
In The Last Decade
Mark J. van der Laan
312 papers receiving 11.5k citations
Hit Papers
Peers
Comparison fields: 5 of 210
- Statistics and Probability 6.9k
- Economics and Econometrics 1.7k
- Artificial Intelligence 1.4k
- Molecular Biology 1.2k
- Epidemiology 751
Countries citing papers authored by Mark J. van der Laan
This map shows the geographic impact of Mark J. van der Laan'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 Mark J. van der Laan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark J. van der Laan more than expected).
Fields of papers citing papers by Mark J. van der Laan
This network shows the impact of papers produced by Mark J. van der Laan. 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 Mark J. van der Laan. The network helps show where Mark J. van der Laan may publish in the future.
Co-authorship network of co-authors of Mark J. van der Laan
This figure shows the co-authorship network connecting the top 25 collaborators of Mark J. van der Laan. A scholar is included among the top collaborators of Mark J. van der Laan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mark J. van der Laan. Mark J. van der Laan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 58 | |
| 4 | 8 | |
| 5 | 7 | |
| 6 | 17 | |
| 7 | Robust and flexible estimation of data-dependent stochastic mediation effects: a proposed method and example in a randomized trial setting | 3 |
| 8 | 22 | |
| 9 | 26 | |
| 10 | 15 | |
| 11 | 125 | |
| 12 | tmle: An R Package for Targeted Maximum Likelihood Estimation | 25 |
| 13 | Statistics Ready for a Revolution: Next Generation of Statisticians Must Build Tools for Massive Data Sets | 16 |
| 14 | 372 | |
| 15 | 2 | |
| 16 | Data Adaptive Pathway Testing | 3 |
| 17 | Test Statistics Null Distributions in Multiple Testing: Simulation Studies and Applications to Genomics | 8 |
| 18 | 34 | |
| 19 | 1 | |
| 20 | Inefficient estimators of the bivariate survival function for three models | 86 |
About Mark J. van der Laan
Mark J. van der Laan is a scholar working on Statistics and Probability, Virology and Artificial Intelligence, having authored 317 papers that have together received 12.1k indexed citations. Recurring topics across this work include Statistical Methods and Inference (193 papers), Advanced Causal Inference Techniques (165 papers) and Statistical Methods and Bayesian Inference (143 papers). The work is most often cited by research in Statistics and Probability (6.9k citations), Economics and Econometrics (1.7k citations) and Virology (278 citations). Mark J. van der Laan has collaborated with scholars based in United States, France and Denmark. Frequent co-authors include Sandrine Dudoit, Alan Hubbard, Susan Gruber, Eric C. Polley, Sherri Rose, Maya L. Petersen, Daniel B. Rubin, Katherine S. Pollard, Sandra E. Sinisi and Maya Petersen. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Bioinformatics.
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.