Baoluo Sun

958 total citations
19 papers, 561 citations indexed

About

Baoluo Sun is a scholar working on Statistics and Probability, Genetics and Sociology and Political Science. According to data from OpenAlex, Baoluo Sun has authored 19 papers receiving a total of 561 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Statistics and Probability, 5 papers in Genetics and 3 papers in Sociology and Political Science. Recurrent topics in Baoluo Sun's work include Statistical Methods and Inference (12 papers), Statistical Methods and Bayesian Inference (11 papers) and Advanced Causal Inference Techniques (9 papers). Baoluo Sun is often cited by papers focused on Statistical Methods and Inference (12 papers), Statistical Methods and Bayesian Inference (11 papers) and Advanced Causal Inference Techniques (9 papers). Baoluo Sun collaborates with scholars based in United States, Singapore and China. Baoluo Sun's co-authors include Eric J. Tchetgen Tchetgen, Ofer Harel, Enrique F. Schisterman, Stephen R. Cole, Neil J. Perkins, Emily M. Mitchell, Eric Tchetgen Tchetgen, Lan Liu, Wang Miao and Linbo Wang and has published in prestigious journals such as Journal of the American Statistical Association, Bioinformatics and American Journal of Epidemiology.

In The Last Decade

Baoluo Sun

19 papers receiving 555 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Baoluo Sun United States 9 185 67 60 60 51 19 561
Maryam Nazemipour Iran 15 151 0.8× 35 0.5× 42 0.7× 102 1.7× 90 1.8× 42 865
Shahab Jolani Netherlands 10 152 0.8× 65 1.0× 86 1.4× 23 0.4× 82 1.6× 30 793
Panteha Hayati Rezvan United States 11 82 0.4× 27 0.4× 61 1.0× 103 1.7× 67 1.3× 31 568
Lueping Zhao United States 10 320 1.7× 22 0.3× 95 1.6× 59 1.0× 47 0.9× 13 740
Sandra E. Sinisi United States 8 322 1.7× 26 0.4× 39 0.7× 32 0.5× 37 0.7× 10 669
Emily M. Mitchell United States 14 128 0.7× 68 1.0× 90 1.5× 263 4.4× 60 1.2× 33 887
Matteo Quartagno United Kingdom 14 193 1.0× 32 0.5× 59 1.0× 60 1.0× 86 1.7× 39 715
Zhehui Luo United States 9 65 0.4× 43 0.6× 88 1.5× 78 1.3× 43 0.8× 12 490
Timothy M. Morgan United States 13 126 0.7× 80 1.2× 89 1.5× 63 1.1× 65 1.3× 21 584
Gareth J Griffith United Kingdom 8 41 0.2× 86 1.3× 76 1.3× 26 0.4× 68 1.3× 25 615

Countries citing papers authored by Baoluo Sun

Since Specialization
Citations

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

Fields of papers citing papers by Baoluo Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Baoluo Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Baoluo Sun. A scholar is included among the top collaborators of Baoluo Sun 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 Baoluo Sun. Baoluo Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Ye, Ting, Zhonghua Liu, Baoluo Sun, & Eric Tchetgen Tchetgen. (2024). GENIUS-MAWII: for robust Mendelian randomization with many weak invalid instruments. Journal of the Royal Statistical Society Series B (Statistical Methodology). 86(4). 1045–1067. 6 indexed citations
2.
Sun, Baoluo, Zhonghua Liu, & Eric J. Tchetgen Tchetgen. (2023). Semiparametric efficient G-estimation with invalid instrumental variables. Biometrika. 110(4). 953–971. 2 indexed citations
3.
Liu, Zhonghua, et al.. (2022). Mendelian Randomization Mixed-Scale Treatment Effect Robust Identification and Estimation for Causal Inference. Biometrics. 79(3). 2208–2219. 15 indexed citations
4.
Sun, Baoluo, et al.. (2022). Mediation analysis with multiple mediators under unmeasured mediator‐outcome confounding. Statistics in Medicine. 42(4). 422–432. 6 indexed citations
5.
Yue, Mu, Jialiang Li, & Baoluo Sun. (2022). Conditional sparse boosting for high-dimensional instrumental variable estimation. Journal of Statistical Computation and Simulation. 92(15). 3087–3108. 1 indexed citations
6.
Cheng, Qing, Xiaoran Chai, Baoluo Sun, et al.. (2021). MR-Corr2: a two-sample Mendelian randomization method that accounts for correlated horizontal pleiotropy using correlated instrumental variants. Bioinformatics. 38(2). 303–310. 10 indexed citations
7.
Sun, Baoluo & Zhiqiang Tan. (2021). High-Dimensional Model-Assisted Inference for Local Average Treatment Effects With Instrumental Variables. Journal of Business and Economic Statistics. 40(4). 1732–1744. 6 indexed citations
8.
Cheng, Shanshan, Jingjing Lyu, Xian Shi, et al.. (2021). Rare variant association tests for ancestry-matched case-control data based on conditional logistic regression. Briefings in Bioinformatics. 23(2). 4 indexed citations
9.
Sun, Baoluo, et al.. (2019). Doubly Robust Regression Analysis for Data Fusion. Statistica Sinica. 6 indexed citations
10.
Liu, Lan, Wang Miao, Baoluo Sun, James M. Robins, & Eric Tchetgen Tchetgen. (2018). Identification and Inference for Marginal Average Treatment Effect on the Treated with an Instrumental Variable. Statistica Sinica. 30(3). 1517–1541. 5 indexed citations
11.
Tchetgen, Eric J. Tchetgen, et al.. (2017). Semiparametric Estimation with Data Missing Not at Random Using an Instrumental Variable. Statistica Sinica. 28(4). 1965–1983. 23 indexed citations
12.
Dou, Jinzhuang, Baoluo Sun, Xueling Sim, et al.. (2017). Estimation of kinship coefficient in structured and admixed populations using sparse sequencing data. PLoS Genetics. 13(9). e1007021–e1007021. 20 indexed citations
13.
Harel, Ofer, Emily M. Mitchell, Neil J. Perkins, et al.. (2017). Multiple Imputation for Incomplete Data in Epidemiologic Studies. American Journal of Epidemiology. 187(3). 576–584. 172 indexed citations
14.
Tchetgen, Eric Tchetgen, Linbo Wang, & Baoluo Sun. (2017). Discrete Choice Models for Nonmonotone Nonignorable Missing Data: Identification and Inference. Statistica Sinica. 28(4). 2069–2088. 15 indexed citations
15.
Perkins, Neil J., Stephen R. Cole, Ofer Harel, et al.. (2017). Principled Approaches to Missing Data in Epidemiologic Studies. American Journal of Epidemiology. 187(3). 568–575. 169 indexed citations
16.
Sun, Baoluo, Neil J. Perkins, Stephen R. Cole, et al.. (2017). Inverse-Probability-Weighted Estimation for Monotone and Nonmonotone Missing Data. American Journal of Epidemiology. 187(3). 585–591. 39 indexed citations
17.
Sun, Baoluo, Tyler J. VanderWeele, & Eric J. Tchetgen Tchetgen. (2017). A Multinomial Regression Approach to Model Outcome Heterogeneity. American Journal of Epidemiology. 186(9). 1097–1103. 8 indexed citations
18.
Sun, Baoluo & Eric J. Tchetgen Tchetgen. (2016). On Inverse Probability Weighting for Nonmonotone Missing at Random Data. Journal of the American Statistical Association. 113(521). 369–379. 48 indexed citations
19.
Liu, Lan, Wang Miao, Baoluo Sun, James M. Robins, & Eric Tchetgen Tchetgen. (2015). Identification and Inference for Marginal Average Treatment Effect on the Treated With an Instrumental Variable. arXiv (Cornell University). 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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