Suojin Wang

3.6k total citations
168 papers, 2.6k citations indexed

About

Suojin Wang is a scholar working on Statistics and Probability, General Health Professions and Artificial Intelligence. According to data from OpenAlex, Suojin Wang has authored 168 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Statistics and Probability, 31 papers in General Health Professions and 28 papers in Artificial Intelligence. Recurrent topics in Suojin Wang's work include Statistical Methods and Inference (57 papers), Statistical Methods and Bayesian Inference (54 papers) and Advanced Statistical Methods and Models (25 papers). Suojin Wang is often cited by papers focused on Statistical Methods and Inference (57 papers), Statistical Methods and Bayesian Inference (54 papers) and Advanced Statistical Methods and Models (25 papers). Suojin Wang collaborates with scholars based in United States, China and Saudi Arabia. Suojin Wang's co-authors include Robert J. Buchanan, C. Y. Wang, Marcia G. Ory, Raymond J. Carroll, Chunfeng Huang, Chanam Lee, Abdulhakim A. Qahtan, Xiangliang Zhang, Naisyin Wang and Myungsuk Kim and has published in prestigious journals such as Journal of the American Statistical Association, Bioinformatics and Biometrics.

In The Last Decade

Suojin Wang

159 papers receiving 2.5k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Suojin Wang 902 351 328 308 257 168 2.6k
Toshiro Tango 443 0.5× 234 0.7× 554 1.7× 308 1.0× 534 2.1× 134 4.1k
Purushottam W. Laud 855 0.9× 598 1.7× 441 1.3× 387 1.3× 348 1.4× 132 4.0k
Brian Neelon 503 0.6× 203 0.6× 813 2.5× 483 1.6× 294 1.1× 124 2.9k
Peter X.‐K. Song 1.1k 1.2× 520 1.5× 405 1.2× 379 1.2× 425 1.7× 199 5.1k
Johannes Ledolter 607 0.7× 312 0.9× 171 0.5× 152 0.5× 632 2.5× 160 4.7k
Jeff Goldsmith 602 0.7× 283 0.8× 311 0.9× 147 0.5× 108 0.4× 134 3.8k
Shaun R. Seaman 1.2k 1.4× 297 0.8× 546 1.7× 384 1.2× 373 1.5× 91 5.2k
Paul Gustafson 1.5k 1.7× 370 1.1× 223 0.7× 185 0.6× 491 1.9× 194 3.6k
Gianluca Baio 499 0.6× 121 0.3× 608 1.9× 750 2.4× 1.0k 4.0× 167 4.7k
Donglin Zeng 2.4k 2.7× 585 1.7× 411 1.3× 215 0.7× 501 1.9× 328 6.2k

Countries citing papers authored by Suojin Wang

Since Specialization
Citations

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

Fields of papers citing papers by Suojin Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suojin Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Suojin Wang. A scholar is included among the top collaborators of Suojin Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Suojin Wang. Suojin Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Suojin, et al.. (2024). Optimal model averaging for partially linear models with missing response variables and error‐prone covariates. Statistics in Medicine. 43(22). 4328–4348.
2.
Cai, Li, Yao Yao, & Suojin Wang. (2023). Oracle-efficient estimation for the mean function of missing covariate data based on noparametrically estimated selection probabilities. Journal of nonparametric statistics. 36(4). 1018–1035. 1 indexed citations
3.
Miller, Daniel S., et al.. (2015). A Comparison of Some Approximate Confidence Intervals for a Single Proportion for Clustered Binary Outcome Data. The International Journal of Biostatistics. 12(2). 14 indexed citations
4.
Long, Quan, et al.. (2014). A Laplace method for under-determined Bayesian optimal experimental designs. Computer Methods in Applied Mechanics and Engineering. 285. 849–876. 18 indexed citations
5.
Wang, Suojin, et al.. (2014). Variable selection and estimation for longitudinal survey data. Journal of Multivariate Analysis. 130. 409–424. 5 indexed citations
6.
Lu, Wenhua, E. Lisako J. McKyer, Chanam Lee, et al.. (2014). Perceived barriers to children’s active commuting to school: a systematic review of empirical, methodological and theoretical evidence. International Journal of Behavioral Nutrition and Physical Activity. 11(1). 140–140. 89 indexed citations
7.
Smith, Matthew Lee, Angela K. Hochhalter, Yichen Cheng, Suojin Wang, & Marcia G. Ory. (2011). Programmatic influences on outcomes of an evidence-based fall prevention program for older adults: a translational assessment. Translational Behavioral Medicine. 1(3). 384–393. 16 indexed citations
8.
Wang, Li & Suojin Wang. (2011). Nonparametric additive model-assisted estimation for survey data. Journal of Multivariate Analysis. 102(7). 1126–1140. 14 indexed citations
9.
Buchanan, Robert J., et al.. (2006). Urban/rural differences in access and barriers to health care for people with multiple sclerosis.. PubMed. 29(3). 360–75. 29 indexed citations
10.
Sharkey, Joseph R., Marcia G. Ory, & Suojin Wang. (2006). Double Strain of Severe Obesity and Depression on Perception of Increased Diabetes Burden Among Homebound Older Women. Journal of Nutrition for the Elderly. 26(1-2). 123–130. 3 indexed citations
11.
Wu, Chengcang, Suojin Wang, & Hong‐Bin Zhang. (2006). Interactions among genomic structure, function, and evolution revealed by comprehensive analysis of the Arabidopsis thaliana genome. Genomics. 88(4). 394–406. 7 indexed citations
12.
Eubank, R. L., Chin‐Shang Li, & Suojin Wang. (2005). TESTING LACK-OF-FIT OF PARAMETRIC REGRESSION MODELS USING NONPARAMETRIC REGRESSION TECHNIQUES. Statistica Sinica. 15(1). 135–152. 10 indexed citations
13.
Buchanan, Robert J., et al.. (2004). Analyses of nursing home residents with multiple sclerosis at admission and one year after admission. Multiple Sclerosis Journal. 10(1). 74–79. 15 indexed citations
14.
Buchanan, Robert J., Suojin Wang, & Chunfeng Huang. (2002). Analyses of Nursing Home Residents with Human Immunodeficiency Virus and Depression Using the Minimum Data Set. AIDS Patient Care and STDs. 16(9). 441–455. 9 indexed citations
15.
Buchanan, Robert J., Suojin Wang, & Chunfeng Huang. (2002). Profiles of Nursing Home Residents with HIV. Journal of Health Care for the Poor and Underserved. 13(3). 379–391. 20 indexed citations
16.
Buchanan, Robert J., Suojin Wang, & Chunfeng Huang. (2001). Nursing Home Residents with HIV and Anemia. AIDS Patient Care and STDs. 15(7). 373–383. 6 indexed citations
17.
Wang, C. Y., et al.. (1997). Weighted Semiparametric Estimation in Regression Analysis with Missing Covariate Data. Journal of the American Statistical Association. 92(438). 512–525. 94 indexed citations
18.
Eubank, R. L. & Suojin Wang. (1994). Confidence regions in non-parametric regression. Scandinavian Journal of Statistics. 21(2). 147–157. 12 indexed citations
19.
Gray, H. L. & Suojin Wang. (1991). A General Method for Approximating Tail Probabilities. Journal of the American Statistical Association. 86(413). 159–166. 8 indexed citations
20.
Wang, Suojin. (1989). On the bootstrap and smoothed bootstrap. Communication in Statistics- Theory and Methods. 18(11). 3949–3962. 6 indexed citations

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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