Lingling Li

696 total citations
18 papers, 426 citations indexed

About

Lingling Li is a scholar working on Statistics and Probability, Artificial Intelligence and Mathematical Physics. According to data from OpenAlex, Lingling Li has authored 18 papers receiving a total of 426 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistics and Probability, 3 papers in Artificial Intelligence and 2 papers in Mathematical Physics. Recurrent topics in Lingling Li's work include Statistical Methods in Clinical Trials (12 papers), Statistical Methods and Inference (9 papers) and Statistical Methods and Bayesian Inference (7 papers). Lingling Li is often cited by papers focused on Statistical Methods in Clinical Trials (12 papers), Statistical Methods and Inference (9 papers) and Statistical Methods and Bayesian Inference (7 papers). Lingling Li collaborates with scholars based in United States, Netherlands and United Kingdom. Lingling Li's co-authors include Changyu Shen, James M. Robins, Martin Kulldorff, Xiaochun Li, Scott Evans, Aad van der Vaart, Eric Tchetgen Tchetgen, Xiaochun Li, Ann Chen Wu and Rajarshi Mukherjee and has published in prestigious journals such as American Journal of Epidemiology, Statistics in Medicine and The Annals of Statistics.

In The Last Decade

Lingling Li

17 papers receiving 411 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lingling Li United States 12 255 73 56 50 33 18 426
Xiaofeng Zhou United States 13 58 0.2× 67 0.9× 153 2.7× 64 1.3× 40 1.2× 24 475
Stella Stergiopoulos United States 12 41 0.2× 123 1.7× 69 1.2× 19 0.4× 9 0.3× 28 383
Christine E. Hallgreen Denmark 11 42 0.2× 161 2.2× 34 0.6× 29 0.6× 4 0.1× 29 371
Demissie Alemayehu United States 15 65 0.3× 105 1.4× 5 0.1× 58 1.2× 14 0.4× 51 595
Tomas Bergvall Sweden 10 37 0.1× 64 0.9× 236 4.2× 21 0.4× 13 0.4× 12 356
Kristina Juhlin Sweden 12 78 0.3× 92 1.3× 391 7.0× 39 0.8× 12 0.4× 17 554
Samuel Lendle United States 9 149 0.6× 74 1.0× 5 0.1× 54 1.1× 24 0.7× 14 365
Kimberly A. Mc Cord Switzerland 7 30 0.1× 80 1.1× 6 0.1× 35 0.7× 29 0.9× 9 284
Heather M McIntosh United Kingdom 11 36 0.1× 70 1.0× 18 0.3× 45 0.9× 12 0.4× 14 491
Rebecca Noel United States 12 45 0.2× 154 2.1× 25 0.4× 97 1.9× 2 0.1× 20 822

Countries citing papers authored by Lingling Li

Since Specialization
Citations

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

Fields of papers citing papers by Lingling Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingling Li

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

All Works

18 of 18 papers shown
1.
Li, Lingling, et al.. (2019). Exact conditional maximized sequential probability ratio test adjusted for covariates. Sequential Analysis. 38(1). 115–133. 6 indexed citations
2.
Robins, James M., Lingling Li, Rajarshi Mukherjee, Eric Tchetgen Tchetgen, & Aad van der Vaart. (2017). Minimax estimation of a functional on a structured high-dimensional model. The Annals of Statistics. 45(5). 40 indexed citations
3.
Li, Lingling, Shijie Tang, & Liewen Jiang. (2017). On an enhanced rank‐preserving structural failure time model to handle treatment switch, crossover, and dropout. Statistics in Medicine. 36(10). 1532–1547. 5 indexed citations
4.
Li, Lingling, Martin Kulldorff, Estelle Russek‐Cohen, Alison Tse Kawai, & Wei Hua. (2015). Quantifying the impact of time‐varying baseline risk adjustment in the self‐controlled risk interval design. Pharmacoepidemiology and Drug Safety. 24(12). 1304–1312. 5 indexed citations
5.
Toh, Sengwee, Marsha E. Reichman, Monika Houstoun, et al.. (2013). Multivariable confounding adjustment in distributed data networks without sharing of patient‐level data. Pharmacoepidemiology and Drug Safety. 22(11). 1171–1177. 26 indexed citations
6.
Shen, Changyu, Xiaochun Li, & Lingling Li. (2013). Inverse probability weighting for covariate adjustment in randomized studies. Statistics in Medicine. 33(4). 555–568. 27 indexed citations
7.
Cook, Andrea J., Ram C. Tiwari, Robert Wellman, et al.. (2012). Statistical approaches to group sequential monitoring of postmarket safety surveillance data: current state of the art for use in the Mini‐Sentinel pilot. Pharmacoepidemiology and Drug Safety. 21(S1). 72–81. 33 indexed citations
8.
Shen, Changyu, Xiaochun Li, Lingling Li, & Martin C. Were. (2011). Sensitivity analysis for causal inference using inverse probability weighting. Biometrical Journal. 53(5). 822–837. 22 indexed citations
9.
Li, Lingling, Changyu Shen, Ann Chen Wu, & Xiaochun Li. (2011). Propensity Score-based Sensitivity Analysis Method for Uncontrolled Confounding. American Journal of Epidemiology. 174(3). 345–353. 35 indexed citations
10.
Li, Lingling, Changyu Shen, Xiaochun Li, & James M. Robins. (2011). On weighting approaches for missing data. Statistical Methods in Medical Research. 22(1). 14–30. 70 indexed citations
11.
Li, Lingling, Eric Tchetgen Tchetgen, Aad van der Vaart, & James M. Robins. (2011). Higher order inference on a treatment effect under low regularity conditions. Statistics & Probability Letters. 81(7). 821–828. 8 indexed citations
12.
Li, Lingling, Martin Kulldorff, Jennifer C. Nelson, & Andrea J. Cook. (2011). A Propensity Score-Enhanced Sequential Analytic Method for Comparative Drug Safety Surveillance. Statistics in Biosciences. 3(1). 45–62. 4 indexed citations
13.
Wang, Lidong, Lingling Li, & Jiu Ding. (2010). Uniform Convergence, Mixing and Chaos. 2(1). 73–79. 1 indexed citations
14.
Robins, James M., Eric Tchetgen Tchetgen, Lingling Li, & Aad van der Vaart. (2009). Semiparametric minimax rates. Electronic Journal of Statistics. 3(none). 1305–1321. 18 indexed citations
15.
Li, Lingling, Scott Evans, Hajime Uno, & L. J. Wei. (2009). Predicted Interval Plots (PIPS): A Graphical Tool for Data Monitoring of Clinical Trials. Statistics in Biopharmaceutical Research. 1(4). 348–355. 13 indexed citations
16.
Li, Lingling & Martin Kulldorff. (2009). A conditional maximized sequential probability ratio test for Pharmacovigilance. Statistics in Medicine. 29(2). 284–295. 57 indexed citations
17.
Robins, James M., Lingling Li, Eric J. Tchetgen Tchetgen, & Aad van der Vaart. (2008). Quadratic semiparametric Von Mises calculus. Metrika. 69(2-3). 227–247. 20 indexed citations
18.
Evans, Scott & Lingling Li. (2004). A comparison of goodness of fit tests for the logistic GEE model. Statistics in Medicine. 24(8). 1245–1261. 36 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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