G‐estimation of structural nested restricted mean time lost models to estimate effects of time‐varying treatments on a failure time outcome-Reference-Cited by-同舟云学术

G‐estimation of structural nested restricted mean time lost models to estimate effects of time‐varying treatments on a failure time outcome

Published:2019-12-26 Issue:3 Volume:76 Page:799-810
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Hagiwara Yasuhiro¹^ORCID,Shinozaki Tomohiro²,Matsuyama Yutaka¹

Affiliation:

1. Department of Biostatistics School of Public Health The University of Tokyo Tokyo Japan

2. Department of Information and Computer Technology Faculty of Engineering Tokyo University of Science Tokyo Japan

Funder

Ministry of Health, Labour and Welfare

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.13200

Reference27 articles.

1. Regression Analysis of Restricted Mean Survival Time Based on Pseudo-Observations

2. Causal Inference on the Difference of the Restricted Mean Lifetime Between Two Groups

3. Estimating effects from randomized trials with discontinuations: the need for intent-to-treat design and G-estimation

4. Structural accelerated failure time models for survival analysis in studies with time-varying treatments

5. G-Estimation and Artificial Censoring: Problems, Challenges, and Applications

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