Survival Modelling for Data From Combined Cohorts: Opening the Door to Meta Survival Analyses and Survival Analysis Using Electronic Health Records-Reference-Cited by-同舟云学术

Survival Modelling for Data From Combined Cohorts: Opening the Door to Meta Survival Analyses and Survival Analysis Using Electronic Health Records

Published:2022-06-16 Issue:1 Volume:91 Page:72-87
ISSN:0306-7734
Container-title:International Statistical Review
language:en
Short-container-title:Int Statistical Rev

Author:

McVittie James H.¹^ORCID,Best Ana F.²,Wolfson David B.¹,Stephens David A.¹,Wolfson Julian³,Buckeridge David L.⁴,Gadalla Shahinaz M.⁵

Affiliation:

1. Department of Mathematics and Statistics McGill University Montreal Quebec Canada

2. Biostatistics Branch, Biometrics Research Program Division of Cancer Treatment and Diagnosis National Cancer Institute National Institutes of Health Bethesda MD USA

3. School of Public Health, Division of Biostatistics University of Minnesota Minneapolis MN USA

4. Department of Epidemiology, Biostatistics and Occupational Health McGill University Montreal Quebec Canada

5. Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Bethesda MD USA

Funder

National Cancer Institute

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/insr.12510

Reference36 articles.

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2. Length-Biased Sampling With Right Censoring

3. Data mining for censored time-to-event data: a Bayesian network model for predicting cardiovascular risk from electronic health record data

4. Acceleration of Expectation-Maximization algorithm for length-biased right-censored data

5. Efron B.(1967).The two sample problem with censored data. InProceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability Vol.4 pp.831–852.

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