A flexible sensitivity analysis approach for unmeasured confounding with multiple treatments and a binary outcome with application to SEER-Medicare lung cancer data-Reference-Cited by-同舟云学术

A flexible sensitivity analysis approach for unmeasured confounding with multiple treatments and a binary outcome with application to SEER-Medicare lung cancer data

Published:2022-06-01 Issue:2 Volume:16 Page:
ISSN:1932-6157
Container-title:The Annals of Applied Statistics
language:
Short-container-title:Ann. Appl. Stat.

Author:

Hu Liangyuan¹,Zou Jungang²,Gu Chenyang³,Ji Jiayi⁴,Lopez Michael⁵,Kale Minal⁶

Affiliation:

1. Department of Biostatistics and Epidemiology, Rutgers University

2. Department of Biostatistics, Columbia University

3. Department of Biostatistics, Brown University

4. Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai

5. Department of Mathematics, Skidmore College

6. Department of Medicine, Icahn School of Medicine at Mount Sinai

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Reference43 articles.

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4. BRUMBACK, B. A., HERNÁN, M. A., HANEUSE, S. J. and ROBINS, J. M. (2004). Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures. Stat. Med. 23 749–767.

5. CEPPA, D. P., KOSINSKI, A. S., BERRY, M. F., TONG, B. C., HARPOLE, D. H., MITCHELL, J. D., D’AMICO, T. A. and ONAITIS, M. W. (2012). Thoracoscopic lobectomy has increasing benefit in patients with poor pulmonary function: A Society of Thoracic Surgeons Database analysis. Ann. Surg. 256 487–493.

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