Jane Candlish
Impact in
- Statistics and Probability top 10%
- Advanced Causal Inference Techniques
- Statistical Methods in Clinical Trials
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- Meta-analysis and systematic reviews
Papers in
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- Health Systems, Economic Evaluations, Quality of Life 3
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- Advanced Causal Inference Techniques 2
- Statistical Methods in Clinical Trials 2
- Co-authors
- Matthew Sperrin (2 shared papers)Andrew G. Renehan (1 shared paper)Ellena Badrick (1 shared paper)Iain Buchan (1 shared paper)Stephen J. Walters (2 shared papers)Inês B. Henriques (1 shared paper)Richard Jacques (1 shared paper)M. Dawn Teare (2 shared papers)
- Journals
- BMC Medical Research Methodology (2 papers)Trials (2 papers)Epidemiology (1 paper)PubMed (1 paper)
- Partner nations
- United KingdomNetherlands
In The Last Decade
Jane Candlish
6 papers receiving 205 citations
Peers
Comparison fields: 5 of 83
- Statistics and Probability 24
- Statistics, Probability and Uncertainty 17
- Geriatrics and Gerontology 6
- Cardiology and Cardiovascular Medicine 32
- Oncology 34
Countries citing papers authored by Jane Candlish
This map shows the geographic impact of Jane Candlish'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 Jane Candlish with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jane Candlish more than expected).
Fields of papers citing papers by Jane Candlish
This network shows the impact of papers produced by Jane Candlish. 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 Jane Candlish. The network helps show where Jane Candlish may publish in the future.
Co-authors
The 16 scholars most cited alongside Jane Candlish, 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 | 2016 | 88 | |
| 2 | 2019 | 49 | |
| 3 | 2018 | 37 | |
| 4 | 2016 | 20 | |
| 5 | 2019 | 9 | |
| 6 | What makes a good doctor--views of non-medical professionals. | 1998 | 5 |
About Jane Candlish
Jane Candlish is a scholar working on Economics and Econometrics, Statistics and Probability, General Health Professions, Health and Pediatrics, Perinatology and Child Health, having authored 6 papers that have together received 208 indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (3 papers), Advanced Causal Inference Techniques (2 papers), Statistical Methods in Clinical Trials (2 papers), Health Policy Implementation Science (1 paper), Birth, Development, and Health (1 paper), Primary Care and Health Outcomes (1 paper), Delphi Technique in Research (1 paper) and Meta-analysis and systematic reviews (1 paper). The work is most often cited by research in Statistics and Probability (24 citations), Statistics, Probability and Uncertainty (17 citations), Geriatrics and Gerontology (6 citations), Cardiology and Cardiovascular Medicine (32 citations) and Oncology (34 citations). Jane Candlish has collaborated with scholars based in United Kingdom and Netherlands. Frequent co-authors include Matthew Sperrin, Andrew G. Renehan, Ellena Badrick, Iain Buchan, Stephen J. Walters, Inês B. Henriques, Richard Jacques, M. Dawn Teare, Nikki Totton and Laura Mandefield. Their work appears in journals such as BMC Medical Research Methodology, Trials, Epidemiology and PubMed.
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.