Ingeborg Waernbaum
Impact in
- Internal Medicine top 5%
- Venous Thromboembolism Diagnosis and Management
- Statistics and Probability top 2%
- Advanced Causal Inference Techniques
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
Papers in
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- Advanced Causal Inference Techniques 19
- Statistical Methods and Inference 16
- Statistical Methods and Bayesian Inference 12
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- Diabetes Management and Research 5
- Co-authors
- Gisela Dahlquist (7 shared papers)Torbjörn Lind (6 shared papers)Jan W. Eriksson (3 shared papers)Anna Möllsten (6 shared papers)Margareta Norberg (1 shared paper)Xavier de Luna (4 shared papers)Thomas S. Richardson (1 shared paper)Hans J. Arnqvist (3 shared papers)
In The Last Decade
Ingeborg Waernbaum
33 papers receiving 920 citations
Peers
Comparison fields: 5 of 96
- Internal Medicine 94
- Statistics and Probability 167
- Endocrinology, Diabetes and Metabolism 204
- Nephrology 74
- Genetics 218
Countries citing papers authored by Ingeborg Waernbaum
This map shows the geographic impact of Ingeborg Waernbaum'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 Ingeborg Waernbaum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ingeborg Waernbaum more than expected).
Fields of papers citing papers by Ingeborg Waernbaum
This network shows the impact of papers produced by Ingeborg Waernbaum. 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 Ingeborg Waernbaum. The network helps show where Ingeborg Waernbaum may publish in the future.
Co-authors
The 25 scholars most cited alongside Ingeborg Waernbaum, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 184 | |
| 2 | 2005 | 178 | |
| 3 | 2003 | 90 | |
| 4 | 2011 | 87 | |
| 5 | 2010 | 73 | |
| 6 | 2006 | 52 | |
| 7 | 2012 | 50 | |
| 8 | 2019 | 43 | |
| 9 | 2018 | 22 | |
| 10 | 2015 | 19 | |
| 11 | 2023 | 16 | |
| 12 | 2015 | 16 | |
| 13 | 2010 | 11 | |
| 14 | 2013 | 10 | |
| 15 | 2014 | 10 | |
| 16 | 2015 | 10 | |
| 17 | 2016 | 10 | |
| 18 | 2022 | 9 | |
| 19 | 2022 | 7 | |
| 20 | 2014 | 7 |
About Ingeborg Waernbaum
Ingeborg Waernbaum is a scholar working on Statistics and Probability, Endocrinology, Diabetes and Metabolism, Economics and Econometrics, Genetics and Nephrology, having authored 36 papers that have together received 948 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (19 papers), Statistical Methods and Inference (16 papers), Statistical Methods and Bayesian Inference (12 papers), Diabetes Management and Research (5 papers), Diabetes and associated disorders (4 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers), Chronic Kidney Disease and Diabetes (3 papers) and Injury Epidemiology and Prevention (2 papers). The work is most often cited by research in Internal Medicine (94 citations), Statistics and Probability (167 citations), Endocrinology, Diabetes and Metabolism (204 citations), Nephrology (74 citations) and Genetics (218 citations). Ingeborg Waernbaum has collaborated with scholars based in Sweden, Belgium and Denmark. Frequent co-authors include Gisela Dahlquist, Torbjörn Lind, Jan W. Eriksson, Anna Möllsten, Margareta Norberg, Xavier de Luna, Thomas S. Richardson, Hans J. Arnqvist, Maria Svensson and Lennarth Nyström. Their work appears in journals such as Statistics in Medicine, Diabetologia, Diabetes Care, Diabetes and European Journal of Epidemiology.
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.