Ji An

1.4k citations
9 papers · 996 indexed · 2 hit papers · h-index 9

Impact in

Papers in

Ji An

9 papers receiving 963 citations

Hit Papers

Measuring vaccine hesitancy, confidence, trust and flu vaccine uptake: Results of a national survey of White and African American adults 2019 · 220 citations
220201720262020202350100150200250

Peers

Ji An
Comparison fields: 5 of 103
  • Health 608
  • Modeling and Simulation 125
  • Infectious Diseases 183
  • Applied Psychology 41
  • Sociology and Political Science 315
Replace Lauren Dayton with:
Lauren Dayton United States
Karen Hilyard United States
Bao Sheng Loe United Kingdom
Umair Majid Canada
Jeanine P. D. Guidry United States
Alexandra Budenz United States
Michael Wiblishauser United States
Jennifer A. Lueck United States
Mesfin Awoke Bekalu United States
Marta Fadda Switzerland
Ji An relative to Lauren Dayton United States Lauren Dayton's profile →
Citations per field
00.5×10×15.5×
Lauren Dayton · 1×
Citations per year

Countries citing papers authored by Ji An

Since Specialization
Citations

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

Fields of papers citing papers by Ji An

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 7 scholars most cited alongside Ji An, 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 Ji An Line = papers co-authored together Ji An links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 202046
2
Measuring vaccine hesitancy, confidence, trust and flu vaccine uptake: Results of a national survey of White and African American adults
Hit paper breakdown →
2019220
3 201812
4 2017159
5 2017129
6 201755
7 201767
8 201758
9
The Thorny Relation Between Measurement Quality and Fit Index Cutoffs in Latent Variable Models
Hit paper breakdown →
2017250

About Ji An

Ji An is a scholar working on Health, Statistics and Probability, Management Science and Operations Research, Infectious Diseases and Epidemiology, having authored 9 papers that have together received 996 indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (6 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Influenza Virus Research Studies (2 papers), Misinformation and Its Impacts (2 papers), Statistical Methods and Bayesian Inference (1 paper), Respiratory viral infections research (1 paper), Advanced Statistical Modeling Techniques (1 paper) and Diverse Approaches in Healthcare and Education Studies (1 paper). The work is most often cited by research in Health (608 citations), Modeling and Simulation (125 citations), Infectious Diseases (183 citations), Applied Psychology (41 citations) and Sociology and Political Science (315 citations). Ji An has collaborated with scholars based in United States. Frequent co-authors include Gregory R. Hancock, Vicki S. Freimuth, Amelia Jamison, Sandra Crouse Quinn, Daniel McNeish, Donald Musa and Karen Hilyard. Their work appears in journals such as Vaccine, Measurement Interdisciplinary Research and Perspectives, Journal of Personality Assessment, Educational Measurement Issues and Practice and SSM - Population Health.

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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