Eleanor J. Murray
- General Health Professions top 2%
- Statistics and Probability top 1%
- Economics and Econometrics top 5%
- Clinical Psychology top 10%
- Epidemiology
- Co-authors
- Matthew P. FoxMiguel A. HernánPeter W. G. TennantMark S. GilthorpeKellyn F ArnoldEllen C. CanigliaClaire KeebleSarah Gadd
- Topics
- Advanced Causal Inference Techniques (28 papers)Health Systems, Economic Evaluations, Quality of Life (14 papers)COVID-19 epidemiological studies (11 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Eleanor J. Murray
73 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- General Health Professions 499
- Statistics and Probability 310
- Economics and Econometrics 288
- Clinical Psychology 248
- Epidemiology 224
Countries citing papers authored by Eleanor J. Murray
This map shows the geographic impact of Eleanor J. Murray'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 Eleanor J. Murray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eleanor J. Murray more than expected).
Fields of papers citing papers by Eleanor J. Murray
This network shows the impact of papers produced by Eleanor J. Murray. 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 Eleanor J. Murray. The network helps show where Eleanor J. Murray may publish in the future.
Co-authorship network of co-authors of Eleanor J. Murray
This figure shows the co-authorship network connecting the top 25 collaborators of Eleanor J. Murray. A scholar is included among the top collaborators of Eleanor J. Murray 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 Eleanor J. Murray. Eleanor J. Murray is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 26 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 23 | |
| 7 | 4 | |
| 8 | 80 | |
| 9 | 16 | |
| 10 | 1 | |
| 11 | Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendationsbreakdown → | 534 |
| 12 | 9 | |
| 13 | 23 | |
| 14 | 18 | |
| 15 | 50 | |
| 16 | 16 | |
| 17 | 22 | |
| 18 | 27 | |
| 19 | 96 | |
| 20 | Interactive Health Communication Applications for people with chronic disease (Withdrawn Paper. 2004, art. no. CD004274.pub3) | 158 |
About Eleanor J. Murray
Eleanor J. Murray is a scholar working on Statistics and Probability, Modeling and Simulation and Statistics, Probability and Uncertainty, having authored 78 papers that have together received 2.5k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (28 papers), Health Systems, Economic Evaluations, Quality of Life (14 papers) and COVID-19 epidemiological studies (11 papers). The work is most often cited by research in Statistics and Probability (310 citations), Modeling and Simulation (133 citations) and Health Informatics (36 citations). Eleanor J. Murray has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Matthew P. Fox, Miguel A. Hernán, Peter W. G. Tennant, Mark S. Gilthorpe, Kellyn F Arnold, Ellen C. Caniglia, Claire Keeble, Sarah Gadd, Johannes Textor and Laurie Berrie. Their work appears in journals such as New England Journal of Medicine, PLoS ONE and Biochemical Journal.
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.