Wan Tang

3.4k citations
89 papers · 2.3k · h-index 25

Impact in

Papers in

    • Statistical Methods and Bayesian Inference 18
    • Statistical Methods and Inference 14
    • Advanced Causal Inference Techniques 9
    • Statistical Methods in Clinical Trials 7
    • Urinary Tract Infections Management 6

Wan Tang

84 papers receiving 2.2k citations

Peers

Wan Tang
Comparison fields: 5 of 178
  • Neuropsychology and Physiological Psychology 57
  • Health 294
  • Statistics and Probability 195
  • Clinical Psychology 455
  • Obstetrics and Gynecology 147
Replace Mark Oremus with:
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Haroutune K. Armenian United States
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Wan Tang relative to Mark Oremus Canada Mark Oremus's profile →
Citations per field
00.5×4.0×
Mark Oremus · 1×
Citations per year

Countries citing papers authored by Wan Tang

Since Specialization
Citations

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

Fields of papers citing papers by Wan Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011194
2 2016151
3 2010134
4 2015119
5 2007114
6 2011109
7 2006101
8 2012101
9 200883
10 201372
11 201360
12 200956
13 201150
14 201350
15 201246
16 201043
17 201437
18 201035
19 201235
20 201632

About Wan Tang

Wan Tang is a scholar working on Statistics and Probability, Epidemiology, Cardiology and Cardiovascular Medicine, Health and Pediatrics, Perinatology and Child Health, having authored 89 papers that have together received 2.3k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (18 papers), Statistical Methods and Inference (14 papers), Advanced Causal Inference Techniques (9 papers), Statistical Methods in Clinical Trials (7 papers), Urinary Bladder and Prostate Research (6 papers), Urinary Tract Infections Management (6 papers), Bayesian Methods and Mixture Models (5 papers) and Maternal Mental Health During Pregnancy and Postpartum (5 papers). The work is most often cited by research in Neuropsychology and Physiological Psychology (57 citations), Health (294 citations), Statistics and Probability (195 citations), Clinical Psychology (455 citations) and Obstetrics and Gynecology (147 citations). Wan Tang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Xin Tu, Hua He, Thomas G. O’Connor, Emma Robertson Blackmore, Nancy L. Talbot, Yeates Conwell, Jeffrey M. Lyness, Changyong Feng, Linda H. Chaudron and Catherine Cerulli. Their work appears in journals such as Statistical Methods in Medical Research, Statistics in Medicine, Journal of Statistical Planning and Inference, American Journal of Geriatric Psychiatry and Nursing Research.

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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