Sonja Greven

4.1k citations
64 papers · 2.6k · h-index 25

Impact in

Papers in

Sonja Greven

62 papers receiving 2.6k citations

Peers

Sonja Greven
Comparison fields: 5 of 176
  • Statistics and Probability 828
  • Computational Mathematics 25
  • Health, Toxicology and Mutagenesis 344
  • Statistics, Probability and Uncertainty 85
  • Artificial Intelligence 336
Replace Jeff Goldsmith with:
Jeff Goldsmith United States
Fabian Scheipl Germany
Dallas E. Johnson United States
Edward J. Bedrick United States
Yuedong Wang United States
Wensheng Guo United States
Daniel J. Stekhoven Switzerland
Jeng‐Min Chiou Taiwan
Sheng Luo United States
Hannu Oja Finland
Sonja Greven relative to Jeff Goldsmith United States Jeff Goldsmith's profile →
Citations per field
00.5×1.5×1.9×
Jeff Goldsmith · 1×
Citations per year

Countries citing papers authored by Sonja Greven

Since Specialization
Citations

This map shows the geographic impact of Sonja Greven'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 Sonja Greven with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sonja Greven more than expected).

Fields of papers citing papers by Sonja Greven

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sonja Greven. 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 Sonja Greven. The network helps show where Sonja Greven may publish in the future.

Co-authors

The 25 scholars most cited alongside Sonja Greven, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sonja Greven Line = papers co-authored together Sonja Greven links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008274
2 2007245
3 2017218
4 2007218
5 2010174
6 2014151
7 2010133
8 201495
9 200895
10 201285
11 201784
12 200845
13 201443
14 201443
15 201142
16 200739
17 201336
18 202136
19 201435
20 200735

About Sonja Greven

Sonja Greven is a scholar working on Statistics and Probability, Health, Toxicology and Mutagenesis, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 64 papers that have together received 2.6k indexed citations. Recurring topics across this work include Statistical Methods and Inference (24 papers), Statistical Methods and Bayesian Inference (17 papers), Air Quality and Health Impacts (8 papers), Advanced Neuroimaging Techniques and Applications (7 papers), Bayesian Methods and Mixture Models (6 papers), Functional Brain Connectivity Studies (4 papers), Climate Change and Health Impacts (4 papers) and Advanced Statistical Methods and Models (4 papers). The work is most often cited by research in Statistics and Probability (828 citations), Computational Mathematics (25 citations), Health, Toxicology and Mutagenesis (344 citations), Statistics, Probability and Uncertainty (85 citations) and Artificial Intelligence (336 citations). Sonja Greven has collaborated with scholars based in Germany, United States and Sweden. Frequent co-authors include Fabian Scheipl, Helmut Küchenhoff, Ciprian M. Crainiceanu, Thomas Kneib, Ana‐Maria Staicu, Annette Peters, Daniel S. Reich, Brian Caffo, Jeff Goldsmith and Wolfgang Köenig. Their work appears in journals such as Electronic Journal of Statistics, Statistical Modelling, Biometrics, Journal of Computational and Graphical Statistics and Journal of the American Statistical Association.

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.

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