Chenglin Ye

29 papers receiving 1.4k citations

Chenglin Ye's Hit Papers

A tutorial on sensitivity analyses in clinical trials: the what, why, when and how 2013 · 600 citations
6000+4+8Years since publication200400600

Peers

Chenglin Ye
Comparison fields: 5 of 161
  • Statistics, Probability and Uncertainty 161
  • Family Practice 33
  • General Health Professions 332
  • Applied Psychology 63
  • Statistics and Probability 93
Replace Monica Bawor with:
Monica Bawor Canada
Michael Rotondi Canada
Shiyuan Zhang China
Victoria Borg Debono Canada
Kirsty Loudon United Kingdom
Gordon Dooley United Kingdom
Sarah Daisy Kosa Canada
Gernot Wagner Austria
Rogier Donders Netherlands
Anastasia E. Raczek United States
Chenglin Ye relative to Monica Bawor Canada Monica Bawor's profile →
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Countries citing papers authored by Chenglin Ye

Since Specialization
Citations

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

Fields of papers citing papers by Chenglin Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A tutorial on sensitivity analyses in clinical trials: the what, why, when and how
Hit paper breakdown →
2013600
2 2013121
3 2008120
4 201066
5 201461
6 201361
7 201651
8 201447
9 201241
10 201533
11 201627
12 201623
13 201219
14 201217
15 201016
16 201115
17 201713
18 201511
19 201311
20 201710

About Chenglin Ye

Chenglin Ye is a scholar working on Endocrinology, Diabetes and Metabolism, Statistics, Probability and Uncertainty, Public Health, Environmental and Occupational Health, Cardiology and Cardiovascular Medicine and Infectious Diseases, having authored 29 papers that have together received 1.4k indexed citations. Recurring topics across this work include Meta-analysis and systematic reviews (7 papers), Diabetes Treatment and Management (6 papers), Diabetes Management and Research (5 papers), Diabetes Management and Education (3 papers), Advanced Causal Inference Techniques (3 papers), Cardiac, Anesthesia and Surgical Outcomes (3 papers), Ethics in Clinical Research (3 papers) and Delphi Technique in Research (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (161 citations), Family Practice (33 citations), General Health Professions (332 citations), Applied Psychology (63 citations) and Statistics and Probability (93 citations). Chenglin Ye has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Lehana Thabane, Lawrence Mbuagbaw, Shiyuan Zhang, Victoria Borg Debono, Sarah Daisy Kosa, Brittany B. Dennis, Lora Giangregorio, George A. Wells, Rejane Dillenburg and Charles H. Goldsmith. Their work appears in journals such as Contemporary Clinical Trials, BMJ Open, BMC Anesthesiology, Diabetes Care and Canadian Journal of Diabetes.

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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