Fei Wan

4.3k citations
86 papers · 2.3k indexed · 1 hit paper · h-index 24

Fei Wan

79 papers receiving 2.2k citations

Hit Papers

A Randomized, Controlled Trial of Financial Incentives fo...6022009202620142020200400600

Peers

Fei Wan
Comparison fields: 5 of 149
  • Applied Psychology 203
  • General Decision Sciences 46
  • Health 200
  • General Health Professions 484
  • Family Practice 42
Replace Kathryn A. Phillips with:
Kathryn A. Phillips United States
Benjamin M. Craig United States
Marilyn M. Schapira United States
Sarah T. Hawley United States
Andrew N. Freedman United States
Robert F. Nease United States
Kathryn E. Flynn United States
Deb Feldman‐Stewart Canada
Andrew Balshem United States
Elissa M. Ozanne United States
Fei Wan relative to Kathryn A. Phillips United States Kathryn A. Phillips's profile →
Citations per field
00.5×3.4×
Kathryn A. Phillips · 1×
Citations per year

Countries citing papers authored by Fei Wan

Since Specialization
Citations

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

Fields of papers citing papers by Fei Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20258
3 20242
4 20242
5 202443
6 20232
7 20232
8 20232
9 20232
10 20222
11 202125
12 20216
13 202036
14 201912
15 20195
16
The Effect of Firm Marketing Content on Product Sales: Evidence from a Mobile Social Media Platform
201721
17 201416
18 201335
19 201060
20 20097

About Fei Wan

Fei Wan is a scholar working on Statistics and Probability, Oncology, Hematology, Reproductive Medicine and Gastroenterology, having authored 86 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (13 papers), Statistical Methods and Inference (9 papers), Lymphoma Diagnosis and Treatment (8 papers), Health Literacy and Information Accessibility (6 papers), Statistical Methods and Bayesian Inference (6 papers), Health Systems, Economic Evaluations, Quality of Life (5 papers), Mobile Health and mHealth Applications (5 papers) and CAR-T cell therapy research (5 papers). The work is most often cited by research in Applied Psychology (203 citations), General Decision Sciences (46 citations), Health (200 citations), General Health Professions (484 citations) and Family Practice (42 citations). Fei Wan has collaborated with scholars based in United States, China and Colombia. Frequent co-authors include Nandita Mitra, David A. Asch, Robert Galvin, Andrea B. Troxel, Henry A. Glick, Jingsan Zhu, Mark V. Pauly, Andrea Puig, Janet Weiner and Elizabeth L. Corbett. Their work appears in journals such as Blood, Statistics in Medicine, BMC Medical Research Methodology, Biology of Blood and Marrow Transplantation and American Journal of Epidemiology.

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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