Daniel Farewell

3.8k citations
106 papers · 2.6k · h-index 28

Impact in

Papers in

    • Statistical Methods and Bayesian Inference 14
    • Statistical Methods and Inference 11
    • Advanced Causal Inference Techniques 7
    • Statistical Methods in Clinical Trials 6
    • Urinary Tract Infections Management 8

Daniel Farewell

100 papers receiving 2.5k citations

Peers

Daniel Farewell
Comparison fields: 5 of 147
  • Critical Care and Intensive Care Medicine 122
  • Pediatrics, Perinatology and Child Health 477
  • Health 210
  • Emergency Medicine 178
  • Statistics and Probability 186
Replace Scott A. Lorch with:
Scott A. Lorch United States
John J. You Canada
James E. Bost United States
Shantini Paranjothy United Kingdom
Denis Agniel United States
Neera Bhatnagar Canada
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Ricardo M. Fernandes Portugal
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Citations per field
00.5×3.7×
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Citations per year

Countries citing papers authored by Daniel Farewell

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Farewell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Farewell, 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 Daniel Farewell Line = papers co-authored together Daniel Farewell links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019145
2 2011138
3 2009130
4 2010115
5 2014104
6 2013102
7 202094
8 201772
9 201372
10 200970
11 201067
12 201866
13 200763
14 201860
15 201756
16 201154
17 200650
18 201848
19 201346
20 201743

About Daniel Farewell

Daniel Farewell is a scholar working on Statistics and Probability, Epidemiology, Health, General Health Professions and Pediatrics, Perinatology and Child Health, having authored 106 papers that have together received 2.6k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (14 papers), Health disparities and outcomes (12 papers), Statistical Methods and Inference (11 papers), Child Abuse and Related Trauma (9 papers), Urinary Tract Infections Management (8 papers), Employment and Welfare Studies (8 papers), Advanced Causal Inference Techniques (7 papers) and Statistical Methods in Clinical Trials (6 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (122 citations), Pediatrics, Perinatology and Child Health (477 citations), Health (210 citations), Emergency Medicine (178 citations) and Statistics and Probability (186 citations). Daniel Farewell has collaborated with scholars based in United Kingdom, Australia and United States. Frequent co-authors include Sabine Maguire, Alison Kemp, David Fone, Frank Dunstan, Shantini Paranjothy, James White, Laura Cowley, Nick Francis, Ronan A Lyons and Mala Mann. Their work appears in journals such as PLoS ONE, BMJ Open, Child Abuse & Neglect, British Journal of Cancer and PEDIATRICS.

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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