Peiling Yang

876 citations
15 papers · 472 · h-index 9

Impact in

Papers in

    • Treatment of Major Depression 4
    • Statistical Methods in Clinical Trials 3
    • Statistical Methods and Bayesian Inference 2
    • Statistical Methods and Inference 2

Peiling Yang

15 papers receiving 457 citations

Peers

Peiling Yang
Comparison fields: 5 of 72
  • Biological Psychiatry 41
  • Pharmacology 191
  • Psychiatry and Mental health 112
  • Statistics and Probability 45
  • Experimental and Cognitive Psychology 62
Replace Ni A. Khin with:
Ni A. Khin United States
Stephanie Cline United States
Mandy Kromp Germany
André Elferink Netherlands
Kasia Lobello United States
Chamindi Seneviratne United States
Graeme Archer United Kingdom
D Faries United States
Maureen S. Drews United States
J. Wernicke United States
Peiling Yang relative to Ni A. Khin United States Ni A. Khin's profile →
Citations per field
00.5×1.5×
Ni A. Khin · 1×
Citations per year

Countries citing papers authored by Peiling Yang

Since Specialization
Citations

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

Fields of papers citing papers by Peiling Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2011173
2 201493
3 201266
4
Fulvestrant in postmenopausal women with advanced breast cancer.
200346
5 201429
6 201515
7 201511
8 201110
9 201410
10 20108
11 20156
12 20112
13 20201
14 20171
15 20061

About Peiling Yang

Peiling Yang is a scholar working on Pharmacology, Statistics and Probability, Management Science and Operations Research, Psychiatry and Mental health and Surgery, having authored 15 papers that have together received 472 indexed citations. Recurring topics across this work include Treatment of Major Depression (4 papers), Statistical Methods in Clinical Trials (3 papers), Statistical Methods and Bayesian Inference (2 papers), Statistical Methods and Inference (2 papers), Optimal Experimental Design Methods (2 papers), Pain Management and Placebo Effect (1 paper), Estrogen and related hormone effects (1 paper) and Glycosylation and Glycoproteins Research (1 paper). The work is most often cited by research in Biological Psychiatry (41 citations), Pharmacology (191 citations), Psychiatry and Mental health (112 citations), Statistics and Probability (45 citations) and Experimental and Cognitive Psychology (62 citations). Peiling Yang has collaborated with scholars based in United States, Singapore and China. Frequent co-authors include Ni A. Khin, Thomas Laughren, Yeh‐Fong Chen, Yang Yang, Mitchell Mathis, Ellis F. Unger, Yang Yang, Paul A. David, Hung Hung and Robert J. Temple. Their work appears in journals such as The Journal of Clinical Psychiatry, Journal of Biopharmaceutical Statistics, Contemporary Clinical Trials, Journal of the Endocrine Society and International Heart Journal.

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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