🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Susan Gruber

Target (United States)

ORCID: 0000-0003-0127-0099

Also affiliated with Revolution Research, Revolution Medicines (United States), Data Management (Italy)

MathematicsEconomics, Econometrics and Finance

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile
0Author DataRank

Indexed papers

0in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 5 papers. Top paper: “Targeted learning with an undersmoothed LASSO propensity score model for large-scale covariate adjustment in health-care database studies”.

Targeted learning with an undersmoothed LASSO propensity score model for large-scale covariate adjustment in health-care database studies

American Journal of Epidemiology(2024)10.1093/aje/kwae023
N/A
0.406DataRank · unranked
14 citations

Mark van der Laan, Susan Gruber, Xu Shi, Hana Lee, Sarah K. Dutcher +7 more

Note on targeted learning with an undersmoothed Lasso propensity score model for large-scale covariate adjustment in health care database studies

American Journal of Epidemiology(2025)10.1093/aje/kwaf024
N/A
0.165DataRank · unranked
2 citations

Mark van der Laan, Susan Gruber, Xu Shi, Hana Lee, Sarah K. Dutcher +7 more

Can Machine Learning Help Identify Patients at Risk for Recurrent Sexually Transmitted Infections?

Sexually Transmitted Diseases(2020)10.1097/olq.0000000000001264
N/A
0DataRank · unranked
14 citations

Susan Gruber, Sarah J. Willis, Noelle M. Cocoros, Myfanwy Callahan, Elaine W. Flagg +3 more

Change talk subtypes as predictors of alcohol use following brief motivational intervention.

Psychology of Addictive Behaviors(2022)10.1037/adb0000898
N/A
0DataRank · unranked
3 citations

T. T. Janssen, Susan Gruber, Chanelle J. Howe, M Barton Laws, Justin Walthers +4 more

Assessing treatment effects in observational data with missing confounders: A comparative study of practical doubly-robust and traditional missing data methods

arXiv (Cornell University)(2024)10.48550/arxiv.2412.15012
N/A
0DataRank · unranked
1 citations

Chloe Krakauer, Eric Johnson, Susan Gruber, Bryan E. Shepherd, Mark van der Laan +11 more