Susan Gruber

5.0k total citations · 1 hit paper
59 papers, 3.1k citations indexed

About

Susan Gruber is a scholar working on Statistics and Probability, Economics and Econometrics and Epidemiology. According to data from OpenAlex, Susan Gruber has authored 59 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Statistics and Probability, 9 papers in Economics and Econometrics and 8 papers in Epidemiology. Recurrent topics in Susan Gruber's work include Advanced Causal Inference Techniques (36 papers), Statistical Methods and Inference (26 papers) and Statistical Methods and Bayesian Inference (23 papers). Susan Gruber is often cited by papers focused on Advanced Causal Inference Techniques (36 papers), Statistical Methods and Inference (26 papers) and Statistical Methods and Bayesian Inference (23 papers). Susan Gruber collaborates with scholars based in United States, New Zealand and Switzerland. Susan Gruber's co-authors include Mark J. van der Laan, Kristin E. Porter, Michael Klompas, John T. Menchaca, Yue Wang, Maya L. Petersen, Anita Karcz, Chanu Rhee, David J. Murphy and Anthony E. Fiore and has published in prestigious journals such as JAMA, SHILAP Revista de lepidopterología and Clinical Infectious Diseases.

In The Last Decade

Susan Gruber

58 papers receiving 3.0k citations

Hit Papers

Incidence and Trends of Sepsis in US Hospitals Using Clin... 2017 2026 2020 2023 2017 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014
    2017 1.2k citations Chanu Rhee, Raymund Dantes et al. JAMA profile →

Peers

Susan Gruber
Jan Beyersmann Germany
Brian C. Sauer United States
Mark G. Weiner United States
Romain Pirracchio France
Jennifer C. Nelson United States
Robert A. Greevy United States
Keumhee C. Carrière Canada
Glen P. Martin United Kingdom
Stephan Lanes United States
Wim Goettsch Netherlands
Jan Beyersmann Germany
Susan Gruber
Citations per year, relative to Susan Gruber Susan Gruber (= 1×) peers Jan Beyersmann

Countries citing papers authored by Susan Gruber

Since Specialization
Citations

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

Fields of papers citing papers by Susan Gruber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Susan Gruber

This figure shows the co-authorship network connecting the top 25 collaborators of Susan Gruber. A scholar is included among the top collaborators of Susan Gruber 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 Susan Gruber. Susan Gruber 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.
Williamson, Brian D., Susan Gruber, Bryan E. Shepherd, et al.. (2026). Assessing Treatment Effects in Observational Data With Missing Confounders: A Comparative Study of Practical Doubly‐Robust and Traditional Missing Data Methods. Statistics in Medicine. 45(3-5). e70366–e70366.
2.
Nie, Lei, Shiowjen Lee, Haitao Chu, et al.. (2025). Challenges and Possible Strategies to Address Them in Rare Disease Drug Development: A Statistical Perspective. Clinical Pharmacology & Therapeutics. 118(1). 62–73. 1 indexed citations
3.
Gruber, Susan, Haitao Chu, Shiowjen Lee, et al.. (2025). Use of Real‐World Data and Real‐World Evidence in Rare Disease Drug Development: A Statistical Perspective. Clinical Pharmacology & Therapeutics. 117(4). 946–960. 2 indexed citations
4.
Phillips, Rachael V., Mark J. van der Laan, Hana Lee, & Susan Gruber. (2023). Practical considerations for specifying a super learner. International Journal of Epidemiology. 52(4). 1276–1285. 58 indexed citations
5.
Williamson, Brian D., et al.. (2023). An application of the Causal Roadmap in two safety monitoring case studies: Causal inference and outcome prediction using electronic health record data. Journal of Clinical and Translational Science. 7(1). e208–e208. 1 indexed citations
6.
Yoshida, Kazuki, Susan Gruber, Bruce Fireman, & Sengwee Toh. (2018). Comparison of privacy‐protecting analytic and data‐sharing methods: A simulation study. Pharmacoepidemiology and Drug Safety. 27(9). 1034–1041. 14 indexed citations
7.
Rhee, Chanu, Raymund Dantes, Lauren Epstein, et al.. (2017). Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014. JAMA. 318(13). 1241–1241. 1214 indexed citations breakdown →
8.
Laan, Mark van der & Susan Gruber. (2016). One-Step Targeted Minimum Loss-based Estimation Based on Universal Least Favorable One-Dimensional Submodels. The International Journal of Biostatistics. 12(1). 351–378. 20 indexed citations
9.
Schnitzer, Mireille E., Judith J. Lok, & Susan Gruber. (2015). Variable Selection for Confounder Control, Flexible Modeling and Collaborative Targeted Minimum Loss-Based Estimation in Causal Inference. The International Journal of Biostatistics. 12(1). 97–115. 23 indexed citations
10.
Gruber, Susan. (2015). Targeted Learning in Healthcare Research. Big Data. 3(4). 211–218. 5 indexed citations
11.
Gruber, Susan. (2015). A Causal Perspective on OSIM2 Data Generation, with Implications for Simulation Study Design and Interpretation. SHILAP Revista de lepidopterología. 3(2). 177–187. 4 indexed citations
12.
Gruber, Susan & Mark J. van der Laan. (2012). tmle: AnRPackage for Targeted Maximum Likelihood Estimation. Journal of Statistical Software. 51(13). 125 indexed citations
13.
Gruber, Susan & Mark J. van der Laan. (2012). Targeted Minimum Loss Based Estimation of a Causal Effect on an Outcome with Known Conditional Bounds. The International Journal of Biostatistics. 8(1). 21–21. 5 indexed citations
14.
Gruber, Susan & Mark J. van der Laan. (2012). Targeted Minimum Loss Based Estimator that Outperforms a given Estimator. The International Journal of Biostatistics. 8(1). Article 11–Article 11. 18 indexed citations
15.
Gruber, Susan & Mark J. van der Laan. (2011). tmle: An R Package for Targeted Maximum Likelihood Estimation. SHILAP Revista de lepidopterología. 25 indexed citations
16.
Porter, Kristin E., Susan Gruber, Mark J. van der Laan, & Jasjeet S. Sekhon. (2011). The Relative Performance of Targeted Maximum Likelihood Estimators. The International Journal of Biostatistics. 7(1). 74 indexed citations
17.
Petersen, Maya L., Kristin E. Porter, Susan Gruber, Yue Wang, & Mark J. van der Laan. (2010). Diagnosing and responding to violations in the positivity assumption. Statistical Methods in Medical Research. 21(1). 31–54. 372 indexed citations
18.
Gruber, Susan & Mark J. van der Laan. (2010). A Targeted Maximum Likelihood Estimator of a Causal Effect on a Bounded Continuous Outcome. The International Journal of Biostatistics. 6(1). Article 26–Article 26. 103 indexed citations
19.
Gruber, Susan & Mark J. van der Laan. (2010). An Application of Collaborative Targeted Maximum Likelihood Estimation in Causal Inference and Genomics. The International Journal of Biostatistics. 6(1). Article 18–Article 18. 59 indexed citations
20.
Laan, Mark J. van der & Susan Gruber. (2010). Collaborative Double Robust Targeted Maximum Likelihood Estimation. The International Journal of Biostatistics. 6(1). Article 17–Article 17. 121 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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