Dorota M. Dabrowska
- Statistics and Probability top 0.1%
- Artificial Intelligence top 5%
- Economics and Econometrics top 5%
- Immunology
- Molecular Biology
- Co-authors
- Thomas R. FlemingDavid P. HarringtonKjell A. DoksumMarzena GarleyEwa JabłońskaMary M. HorowitzGuo‐Wen SunSławomir Ciesielski
- Topics
- Statistical Methods and Inference (22 papers)Statistical Methods and Bayesian Inference (15 papers)Bayesian Methods and Mixture Models (12 papers)
- Journals
- Journal of the American Statistical AssociationChemosphereInternational Journal of Molecular Sciences
- Partner nations
- United StatesPolandAustralia
In The Last Decade
Dorota M. Dabrowska
41 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Statistics and Probability 2.0k
- Artificial Intelligence 452
- Economics and Econometrics 250
- Immunology 174
- Molecular Biology 167
Countries citing papers authored by Dorota M. Dabrowska
This map shows the geographic impact of Dorota M. Dabrowska'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 Dorota M. Dabrowska with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dorota M. Dabrowska more than expected).
Fields of papers citing papers by Dorota M. Dabrowska
This network shows the impact of papers produced by Dorota M. Dabrowska. 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 Dorota M. Dabrowska. The network helps show where Dorota M. Dabrowska may publish in the future.
Co-authorship network of co-authors of Dorota M. Dabrowska
This figure shows the co-authorship network connecting the top 25 collaborators of Dorota M. Dabrowska. A scholar is included among the top collaborators of Dorota M. Dabrowska 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 Dorota M. Dabrowska. Dorota M. Dabrowska is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 18 | |
| 3 | 19 | |
| 4 | 9 | |
| 5 | 55 | |
| 6 | 28 | |
| 7 | NONPARAMETRIC QUANTILE REGRESSION WITH CENSORED DATA | 7 |
| 8 | 1 | |
| 9 | 24 | |
| 10 | 2 | |
| 11 | 9 | |
| 12 | 6 | |
| 13 | 5 | |
| 14 | 17 | |
| 15 | 14 | |
| 16 | Counting Processes and Survival Analysis.breakdown → | 1605 |
| 17 | 50 | |
| 18 | 207 | |
| 19 | Non-parametric regression with censored survival time data | 135 |
| 20 | 1 |
About Dorota M. Dabrowska
Dorota M. Dabrowska is a scholar working on Statistics and Probability, Artificial Intelligence and Transplantation, having authored 41 papers that have together received 2.8k indexed citations. Recurring topics across this work include Statistical Methods and Inference (22 papers), Statistical Methods and Bayesian Inference (15 papers) and Bayesian Methods and Mixture Models (12 papers). The work is most often cited by research in Statistics and Probability (2.0k citations), Statistics, Probability and Uncertainty (158 citations) and Artificial Intelligence (452 citations). Dorota M. Dabrowska has collaborated with scholars based in United States, Poland and Australia. Frequent co-authors include Thomas R. Fleming, David P. Harrington, Kjell A. Doksum, Marzena Garley, Ewa Jabłońska, Mary M. Horowitz, Guo‐Wen Sun, Sławomir Ciesielski, Wioletta Ratajczak–Wrona and Justyna Możejko‐Ciesielska. Their work appears in journals such as Journal of the American Statistical Association, Chemosphere and International Journal of Molecular Sciences.
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.