Yu‐Sung Su

2.5k total citations · 1 hit paper
22 papers, 1.1k citations indexed

About

Yu‐Sung Su is a scholar working on Statistics and Probability, Political Science and International Relations and Sociology and Political Science. According to data from OpenAlex, Yu‐Sung Su has authored 22 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistics and Probability, 4 papers in Political Science and International Relations and 4 papers in Sociology and Political Science. Recurrent topics in Yu‐Sung Su's work include Statistical Methods and Bayesian Inference (4 papers), Advanced Causal Inference Techniques (4 papers) and Risk and Safety Analysis (3 papers). Yu‐Sung Su is often cited by papers focused on Statistical Methods and Bayesian Inference (4 papers), Advanced Causal Inference Techniques (4 papers) and Risk and Safety Analysis (3 papers). Yu‐Sung Su collaborates with scholars based in China, United States and Italy. Yu‐Sung Su's 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 and has published in prestigious journals such as SHILAP Revista de lepidopterología, Research Policy and Magnetic Resonance in Medicine.

In The Last Decade

Yu‐Sung Su

21 papers receiving 1.1k citations

Hit Papers

Multiple Imputation with Diagnostics (mi) inR: Opening Wi... 2011 2026 2016 2021 2011 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yu‐Sung Su China 12 257 203 133 127 119 22 1.1k
Daniel Freeman United States 13 224 0.9× 227 1.1× 65 0.5× 237 1.9× 53 0.4× 41 1.3k
Shiferaw Gurmu United States 16 299 1.2× 510 2.5× 115 0.9× 112 0.9× 128 1.1× 39 1.1k
Laurie H. Ervin United States 5 233 0.9× 263 1.3× 79 0.6× 304 2.4× 27 0.2× 5 1.4k
Yves Croissant France 10 81 0.3× 516 2.5× 125 0.9× 182 1.4× 57 0.5× 24 1.4k
Richard Goldstein United States 9 104 0.4× 125 0.6× 95 0.7× 98 0.8× 47 0.4× 33 989
Phil Woodward United States 10 259 1.0× 152 0.7× 73 0.5× 45 0.4× 59 0.5× 17 1.0k
Carlos Cinelli United States 9 159 0.6× 238 1.2× 65 0.5× 297 2.3× 56 0.5× 16 1.0k
Lonnie Magee Canada 14 192 0.7× 760 3.7× 136 1.0× 362 2.9× 40 0.3× 30 2.1k
Scott R. Eliason United States 17 160 0.6× 178 0.9× 75 0.6× 536 4.2× 73 0.6× 27 1.4k
Jason Abrevaya United States 22 505 2.0× 737 3.6× 45 0.3× 307 2.4× 94 0.8× 50 1.9k

Countries citing papers authored by Yu‐Sung Su

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Chang, Yu-tzung & Yu‐Sung Su. (2024). Conviction of Multiparty Competition and Elections among Chinese College Students: A List Experiment Study. Journal of Chinese Political Science. 30(2). 195–217. 1 indexed citations
2.
Su, Yu‐Sung & Andrew Gelman. (2023). Who Wants School Vouchers in America? A Comprehensive Study Using Multilevel Regression and Poststratification. Social Sciences. 12(8). 430–430.
3.
Su, Yu‐Sung, et al.. (2023). Re-investigation of the Mediating Effect of Brain Activities between Dispositional Factors and Hazard Recognition: A Multilevel Logistic Regression Approach. KSCE Journal of Civil Engineering. 27(9). 3646–3658. 4 indexed citations
4.
Su, Yu‐Sung, et al.. (2022). How modernization theory has stumbled in China: A political interception perspective. Democratization. 30(2). 302–324. 3 indexed citations
5.
Su, Yu‐Sung, Donald Lien, & Yuling Yao. (2021). Economic growth and happiness in China: A Bayesian multilevel age-period-cohort analysis based on the CGSS data 2005–2015. International Review of Economics & Finance. 77. 191–205. 14 indexed citations
6.
Gelman, Andrew & Yu‐Sung Su. (2020). Data Analysis Using Regression and Multilevel/Hierarchical Models [R package arm version 1.11-2]. 22 indexed citations
7.
Su, Yu‐Sung, et al.. (2020). A Pattern Recognition Framework for Detecting Changes in Chinese Internet Management System. SHILAP Revista de lepidopterología. 1(1). 28–39. 6 indexed citations
8.
Liao, Pin‐Chao, et al.. (2018). Estimating the Influence of Improper Workplace Environment on Human Error: Posterior Predictive Analysis. Advances in Civil Engineering. 2018(1). 9 indexed citations
9.
Bernauer, Thomas, Robert Gampfer, Tianguang Meng, & Yu‐Sung Su. (2016). Could more civil society involvement increase public support for climate policy-making? Evidence from a survey experiment in China. Global Environmental Change. 40. 1–12. 53 indexed citations
10.
Su, Yu‐Sung, et al.. (2015). Missing Data Imputation and Model Checking. 11 indexed citations
13.
Hong, Wei & Yu‐Sung Su. (2012). The effect of institutional proximity in non-local university–industry collaborations: An analysis based on Chinese patent data. Research Policy. 42(2). 454–464. 185 indexed citations
14.
Su, Yu‐Sung, Andrew Gelman, Jennifer Hill, & Masanao Yajima. (2011). Multiple Imputation with Diagnostics (mi) in R: Opening Windows into the Black Box. SHILAP Revista de lepidopterología. 68 indexed citations
15.
Su, Yu‐Sung, Andrew Gelman, Jennifer Hill, & Masanao Yajima. (2011). Multiple Imputation with Diagnostics (mi) inR: Opening Windows into the Black Box. Journal of Statistical Software. 45(2). 483 indexed citations breakdown →
16.
Gelman, Andrew, Lane Kenworthy, & Yu‐Sung Su. (2010). Income Inequality and Partisan Voting in the United States*. Social Science Quarterly. 91(5). 1203–1219. 44 indexed citations
17.
Su, Yu‐Sung, et al.. (2009). What do We Gain? Combining Propensity Score Methods and Multilevel Modeling. SSRN Electronic Journal. 8 indexed citations
18.
Kalkan, Kerem Ozan & Yu‐Sung Su. (2008). A Change in Attitudes Toward Muslims? A Bayesian Investigation of Pre and Post 9/11 Public Opinion. Magnetic Resonance in Medicine. 90(1). 1–25. 1 indexed citations
19.
Su, Yu‐Sung. (2008). It’s easy to produce chartjunk using Microsoft®Excel 2007 but hard to make good graphs. Computational Statistics & Data Analysis. 52(10). 4594–4601. 23 indexed citations
20.
Gelman, Andrew, Aleks Jakulin, Yu‐Sung Su, & Maria Grazia Pittau. (2007). A Default Prior Distribution for Logistic and Other Regression Models. SSRN Electronic Journal. 24 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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