Statistics Collaborative
Impact in
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- Hormonal Regulation and Hypertension
- Diabetes, Cardiovascular Risks, and Lipoproteins
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- Heart Failure Treatment and Management
- Cardiovascular Function and Risk Factors
- Blood Pressure and Hypertension Studies
Papers in
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- Statistical Methods in Clinical Trials 41
- Advanced Causal Inference Techniques 9
- Statistical Methods and Bayesian Inference 8
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- Meta-analysis and systematic reviews 19
- Top scholars
- Janet WittesBertram PittFaı̈ez ZannadRobert CodyA.J. Pérez PérezWillem J. RemmeA CastaigneErnst J. Schaefer
- Journals
- New England Journal of Medicine (11 papers)Clinical Trials (11 papers)Controlled Clinical Trials (9 papers)Statistics in Medicine (9 papers)Vaccine (6 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Statistics Collaborative
211 papers receiving 22.9k citations
Peers
Comparison fields: 5 of 204
- Endocrinology, Diabetes and Metabolism 5.2k
- Cardiology and Cardiovascular Medicine 6.5k
- Nephrology 1.0k
- Pharmacology 2.3k
- Clinical Biochemistry 716
Countries citing scholars working at Statistics Collaborative
This map shows the geographic impact of research produced by authors working at Statistics Collaborative. 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 papers produced at Statistics Collaborative with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Statistics Collaborative more than expected).
Fields of papers published by authors at Statistics Collaborative
This network shows the impact of papers affiliated with Statistics Collaborative at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Statistics Collaborative at the time of their publication.
About Statistics Collaborative
In recent decades, authors affiliated with Statistics Collaborative have published 257 papers, which have received a total of 28.7k indexed citations . Scholars at this organization have produced 45 papers in Statistics and Probability, 20 papers in Statistics, Probability and Uncertainty, 30 papers in Public Health, Environmental and Occupational Health, 5 papers in Virology and 4 papers in Otorhinolaryngology on the topics of Statistical Methods in Clinical Trials (41 papers), Health Systems, Economic Evaluations, Quality of Life (23 papers), Meta-analysis and systematic reviews (19 papers), Ethics in Clinical Research (10 papers), Advanced Causal Inference Techniques (9 papers), Lysosomal Storage Disorders Research (8 papers), Statistical Methods and Bayesian Inference (8 papers) and Retinal Diseases and Treatments (8 papers). Their work is cited by papers focused on Endocrinology, Diabetes and Metabolism (5.2k citations), Cardiology and Cardiovascular Medicine (6.5k citations), Nephrology (1.0k citations), Pharmacology (2.3k citations) and Clinical Biochemistry (716 citations). Authors at Statistics Collaborative collaborate with scholars in United States, United Kingdom and Canada and have published in prestigious journals including New England Journal of Medicine, Clinical Trials, Controlled Clinical Trials, Statistics in Medicine and Vaccine. Some of Statistics Collaborative's most productive authors include Janet Wittes, Janet Wittes, Bertram Pitt, Faı̈ez Zannad, Robert Cody, A.J. Pérez Pérez, Willem J. Remme, A Castaigne, Ernst J. Schaefer and Heidi Christ‐Schmidt.
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.