Yu‐Sung Su
- Statistics and Probability top 2%
- Economics and Econometrics top 5%
- Strategy and Management top 10%
- Sociology and Political Science top 10%
- Artificial Intelligence top 10%
- Co-authors
- Jennifer HillMasanao YajimaAndrew GelmanWei HongLane KenworthyTianguang MengRobert GampferJun S. Liu
- Topics
- Statistical Methods and Bayesian Inference (4 papers)Advanced Causal Inference Techniques (4 papers)Risk and Safety Analysis (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaResearch PolicyMagnetic Resonance in Medicine
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Yu‐Sung Su
21 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Statistics and Probability 257
- Economics and Econometrics 203
- Strategy and Management 133
- Sociology and Political Science 127
- Artificial Intelligence 119
Countries citing papers authored by Yu‐Sung Su
This map shows the geographic impact of Yu‐Sung Su'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 Yu‐Sung Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu‐Sung Su more than expected).
Fields of papers citing papers by Yu‐Sung Su
This network shows the impact of papers produced by Yu‐Sung Su. 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 Yu‐Sung Su. The network helps show where Yu‐Sung Su may publish in the future.
Co-authorship network of co-authors of Yu‐Sung Su
This figure shows the co-authorship network connecting the top 25 collaborators of Yu‐Sung Su. A scholar is included among the top collaborators of Yu‐Sung Su 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 Yu‐Sung Su. Yu‐Sung Su is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 14 | |
| 6 | Data Analysis Using Regression and Multilevel/Hierarchical Models [R package arm version 1.11-2] | 22 |
| 7 | 6 | |
| 8 | 9 | |
| 9 | 53 | |
| 10 | Missing Data Imputation and Model Checking | 11 |
| 11 | 2 | |
| 12 | 47 | |
| 13 | 185 | |
| 14 | 68 | |
| 15 | Multiple Imputation with Diagnostics (mi) inR: Opening Windows into the Black Boxbreakdown → | 483 |
| 16 | 44 | |
| 17 | What do We Gain? Combining Propensity Score Methods and Multilevel Modeling | 8 |
| 18 | 1 | |
| 19 | 23 | |
| 20 | 24 |
About Yu‐Sung Su
Yu‐Sung Su is a scholar working on Statistics and Probability, Medical Laboratory Technology and Radiological and Ultrasound Technology, having authored 22 papers that have together received 1.1k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (4 papers), Advanced Causal Inference Techniques (4 papers) and Risk and Safety Analysis (3 papers). The work is most often cited by research in Statistics and Probability (257 citations), Management of Technology and Innovation (101 citations) and Strategy and Management (133 citations). Yu‐Sung Su has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Jennifer Hill, Masanao Yajima, Andrew Gelman, Wei Hong, Andrew Gelman, Lane Kenworthy, Tianguang Meng, Robert Gampfer, Jun S. Liu and Jonathan Kropko. Their work appears in journals such as SHILAP Revista de lepidopterología, Research Policy and Magnetic Resonance in Medicine.
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.