Bayesian analysis of survival data with missing censoring indicators-Reference-Cited by-同舟云学术

Bayesian analysis of survival data with missing censoring indicators

Published:2020-05-04 Issue:1 Volume:77 Page:305-315
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Brownstein Naomi C.¹²³⁴^ORCID,Bunn Veronica⁴^ORCID,Castro Luis M.⁵⁶⁷^ORCID,Sinha Debajyoti⁴

Affiliation:

1. Department of Biostatistics and Bioinformatics Moffitt Cancer Center Tampa Florida

2. Department of Department of Oncologic Sciences University of South Florida Tampa Florida

3. Department of Behavioral Sciences and Social Medicine Florida State University Tallahassee Florida

4. Department of Statistics Florida State University Tallahassee Florida

5. Department of Statistics Pontificia Universidad Católica de Chile Santiago Chile

6. Millennium Nucleus Center for the Discovery of Structures in Complex Data Santiago Chile

7. Centro de Riesgos y Seguros UC Pontificia Universidad Católica de Chile Santiago Chile

Funder

National Cancer Institute

Gustavus and Louise Pfeiffer Research Foundation

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.13280

Reference16 articles.

1. Study Protocol, Sample Characteristics, and Loss to Follow-Up: The OPPERA Prospective Cohort Study

2. Parameter estimation in Cox models with missing failure indicators and the OPPERA study

3. Canty A.andRipley B.(2016)boot: Bootstrap R (S‐Plus) Functions. R package version 1.3‐18.

4. Analysis of Time-to-Event Data With Incomplete Event Adjudication

5. Regression Models and Life-Tables

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