Weiming Ke

23 papers receiving 292 citations

Peers

Weiming Ke
Comparison fields: 5 of 106
  • Research and Theory 10
  • Genetics 60
  • Family Practice 8
  • Leadership and Management 4
  • Statistics and Probability 21
Replace Arsalan Salari with:
Arsalan Salari Iran
Rick A. Vreman Netherlands
Syed Mohiuddin United Kingdom
Maria Kamusheva Bulgaria
Antonio Carlos Pedroso de Lima Brazil
Samuel T. Savitz United States
Jakub Hlávka United States
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Citations per field
00.5×8.6×
Arsalan Salari · 1×
Citations per year

Countries citing papers authored by Weiming Ke

Since Specialization
Citations

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

Fields of papers citing papers by Weiming Ke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200475
2
Review of the Methods for Handling Missing Data in Longitudinal Data Analysis
201160
3 200732
4 202217
5 201614
6 200412
7 202011
8 201911
9
Statistical Models for Longitudinal Data Analysis
20098
10 20187
11 20087
12 19987
13 20236
14 20206
15 20044
16 20243
17 20173
18 20163
19 20073
20 20193

About Weiming Ke

Weiming Ke is a scholar working on Epidemiology, General Health Professions, Social Psychology, Statistics and Probability and Cardiology and Cardiovascular Medicine, having authored 27 papers that have together received 298 indexed citations. Recurring topics across this work include Medication Adherence and Compliance (3 papers), Statistical Methods and Inference (2 papers), Maternal Mental Health During Pregnancy and Postpartum (2 papers), Statistical Methods and Bayesian Inference (2 papers), Heart Failure Treatment and Management (2 papers), Hepatitis C virus research (2 papers), Liver Disease Diagnosis and Treatment (2 papers) and Psychological Well-being and Life Satisfaction (2 papers). The work is most often cited by research in Research and Theory (10 citations), Genetics (60 citations), Family Practice (8 citations), Leadership and Management (4 citations) and Statistics and Probability (21 citations). Weiming Ke has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Michikazu Nakai, Jianrong Wu, Larry E. Kun, Christine Fuller, Alberto Broniscer, Amar Gajjar, Jocelyn Shealy McGee, Lih-Geeng Chen, Kathryn Osteen and Lingling Yang. Their work appears in journals such as Journal of Pediatric Oncology Nursing, Cancer, Research in Nursing & Health, Cancer Nursing and Chemical and Pharmaceutical Bulletin.

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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