Sebastian Schneeweiss

Statistics and Probability · 2001–2018

A researcher in the Science corpus: 14 papers; trusts 13 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 32 citations into it; #4,149 of 12,932 by trust here, #1,081 by citations
• Economics and Econometrics — 20 citations into it; #14,738 of 23,481 by trust here, #5,522 by citations
• Cardiology and Cardiovascular Medicine — 13 citations into it
• Genetics — 11 citations into it; #6,533 of 6,854 by trust here, #4,743 by citations
• Epidemiology — 10 citations into it; #1,840 of 2,148 by trust here, #772 by citations
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Sebastian Schneeweiss trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Paul R. Rosenbaum
2. Donald B. Rubin
3. M. Cepeda
4. J. Avorn
5. Robert J. Glynn
6. Keisuke Hirano
7. Sander Greenland
8. T. Stürmer
9. Guido W. Imbens
10. James M. Robins

Who trusts Sebastian Schneeweiss overall

1. Peter C. Austin
2. Sudeepa Roy
3. Awa Dieng
4. Elizabeth A. Stuart
5. J. Avorn
6. Cynthia Rudin
7. D. Westreich
8. Feixiong Cheng
9. Tian Bai
10. N. Chesnaye

Papers from Sebastian Schneeweiss's perspective

Ordered by how strongly the researchers Sebastian Schneeweiss trusts endorse each paper. Same corpus, a different order for every researcher.

1. Marginal Structural Models and Causal Inference in Epidemiology
2. Matching using estimated propensity scores: relating theory to practice.
3. Applied Logistic Regression (Technometrics)
4. Estimation of Causal Effects using Propensity Score Weighting: An Application to Data on Right Heart Catheterization (Health Services & Outcomes Research Methodology)
5. Econometric Analysis of Cross Section and Panel Data
6. Gentleman R: R: A language for data analysis and graphics
7. Causal diagrams for epidemiologic research.
8. Adjustment Methods: Propensity Score Methods for Bias Reduction in the Comparison of a Treatment to a Non‐Randomized Control Group
9. The central role of the propensity score in observational studies for causal effects
10. A Prospective, Observational Study of Postmenopausal Hormone Therapy and Primary Prevention of Cardiovascular Disease (Annals of Internal Medicine)

Their papers

• Variable selection for propensity score models. (2006) — 2,278 citations
• Evaluating uses of data mining techniques in propensity score estimation: a simulation study (2008) — 301 citations
• A review of uses of health care utilization databases for epidemiologic research on therapeutics. (2005) — 1,320 citations
• Network-based approach to prediction and population-based validation of in silico drug repurposing (2018) — 487 citations
• A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. (2006) — 722 citations
• High-dimensional propensity score adjustment in studies of treatment effects using health care claims data (2009) — 1,091 citations
• Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics (2006) — 730 citations
• Risk of death in elderly users of conventional vs. atypical antipsychotic medications. (2005) — 972 citations
• Learning from big health care data. (2014) — 306 citations
• Using high‐dimensional propensity scores to automate confounding control in a distributed medical product safety surveillance system (2012) — 115 citations
• Full coverage for preventive medications after myocardial infarction. (2011) — 695 citations
• A combined comorbidity score predicted mortality in elderly patients better than existing scores (2011) — 954 citations
• Repeated hospitalizations predict mortality in the community population with heart failure. (2007) — 598 citations
• Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data. (2001) — 731 citations