Rachel Heyard
Impact in
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- scientometrics and bibliometrics research
- Meta-analysis and systematic reviews
- Statistics and Probability top 10%
- Advanced Causal Inference Techniques
- Statistical Methods in Clinical Trials
Papers in
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- Meta-analysis and systematic reviews 7
- scientometrics and bibliometrics research 6
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- Statistical Methods in Clinical Trials 4
- Advanced Causal Inference Techniques 1
- Co-authors
- Hanna Hottenrott (2 shared papers)Eva Furrer (1 shared paper)Simon Schwab (1 shared paper)Leonhard Held (12 shared papers)Matthias Egger (3 shared papers)Jean‐François Timsit (2 shared papers)Anne Jorstad (1 shared paper)Anna Severin (1 shared paper)
- Journals
- BMJ Open (2 papers)Biometrical Journal (2 papers)eLife (2 papers)BMC Medical Research Methodology (1 paper)PLoS ONE (1 paper)
- Partner nations
- SwitzerlandUnited StatesGermany
In The Last Decade
Rachel Heyard
16 papers receiving 212 citations
Peers
Comparison fields: 5 of 84
- Statistics, Probability and Uncertainty 50
- Statistics and Probability 24
- Information Systems and Management 17
- Gender Studies 15
- Health Informatics 2
Countries citing papers authored by Rachel Heyard
This map shows the geographic impact of Rachel Heyard'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 Rachel Heyard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rachel Heyard more than expected).
Fields of papers citing papers by Rachel Heyard
This network shows the impact of papers produced by Rachel Heyard. 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 Rachel Heyard. The network helps show where Rachel Heyard may publish in the future.
Co-authors
The 25 scholars most cited alongside Rachel Heyard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Good Research Practice | 2019 | 56 |
| 2 | 2021 | 50 | |
| 3 | 2020 | 26 | |
| 4 | 2024 | 14 | |
| 5 | 2019 | 14 | |
| 6 | 2022 | 11 | |
| 7 | 2017 | 11 | |
| 8 | 2018 | 8 | |
| 9 | 2021 | 7 | |
| 10 | 2024 | 4 | |
| 11 | 2023 | 4 | |
| 12 | 2022 | 3 | |
| 13 | 2023 | 3 | |
| 14 | 2025 | 3 | |
| 15 | 2018 | 2 | |
| 16 | 2025 | 1 | |
| 17 | 2025 | 0 | |
| 18 | 2021 | 0 | |
| 19 | 2024 | 0 |
About Rachel Heyard
Rachel Heyard is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability, Artificial Intelligence, Information Systems and Management and Epidemiology, having authored 19 papers that have together received 217 indexed citations. Recurring topics across this work include Meta-analysis and systematic reviews (7 papers), scientometrics and bibliometrics research (6 papers), Statistical Methods in Clinical Trials (4 papers), Machine Learning in Healthcare (2 papers), Scientific Computing and Data Management (2 papers), Sepsis Diagnosis and Treatment (2 papers), Academic Publishing and Open Access (1 paper) and Advanced Causal Inference Techniques (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (50 citations), Statistics and Probability (24 citations), Information Systems and Management (17 citations), Gender Studies (15 citations) and Health Informatics (2 citations). Rachel Heyard has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include Hanna Hottenrott, Eva Furrer, Simon Schwab, Leonhard Held, Matthias Egger, Jean‐François Timsit, Anne Jorstad, Anna Severin, Shirley Wang and Sebastian Schneeweiß. Their work appears in journals such as BMJ Open, Biometrical Journal, eLife, BMC Medical Research Methodology and PLoS ONE.
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.