Bayesian Survival Analysis:
Gespeichert in:
Beteilige Person: | |
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Format: | Elektronisch E-Book |
Sprache: | Englisch |
Veröffentlicht: |
New York, NY
Springer New York
2001
|
Schriftenreihe: | Springer Series in Statistics
|
Schlagwörter: | |
Links: | https://doi.org/10.1007/978-1-4757-3447-8 |
Beschreibung: | Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. Several topics are addressed, including parametric models, semiparametric models based on prior processes, proportional and non-proportional hazards models, frailty models, cure rate models, model selection and comparison, joint models for longitudinal and survival data, models with time varying covariates, missing covariate data, design and monitoring of clinical trials, accelerated failure time models, models for mulitivariate survival data, and special types of hierarchial survival models. Also various censoring schemes are examined including right and interval censored data. Several additional topics are discussed, including noninformative and informative prior specificiations, computing posterior qualities of interest, Bayesian hypothesis testing, variable selection, model selection with nonnested models, model checking techniques using Bayesian diagnostic methods, and Markov chain Monte Carlo (MCMC) algorithms for sampling from the posteiror and predictive distributions. The book presents a balance between theory and applications, and for each class of models discussed, detailed examples and analyses from case studies are presented whenever possible. The applications are all essentially from the health sciences, including cancer, AIDS, and the environment. The book is intended as a graduate textbook or a reference book for a one semester course at the advanced masters or Ph.D. level. This book would be most suitable for second or third year graduate students in statistics or biostatistics. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners |
Umfang: | 1 Online-Ressource (XIV, 480 p) |
ISBN: | 9781475734478 9781441929334 |
ISSN: | 0172-7397 |
DOI: | 10.1007/978-1-4757-3447-8 |
Internformat
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500 | |a Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. Several topics are addressed, including parametric models, semiparametric models based on prior processes, proportional and non-proportional hazards models, frailty models, cure rate models, model selection and comparison, joint models for longitudinal and survival data, models with time varying covariates, missing covariate data, design and monitoring of clinical trials, accelerated failure time models, models for mulitivariate survival data, and special types of hierarchial survival models. Also various censoring schemes are examined including right and interval censored data. Several additional topics are discussed, including noninformative and informative prior specificiations, computing posterior qualities of interest, Bayesian hypothesis testing, variable selection, model selection with nonnested models, model checking techniques using Bayesian diagnostic methods, and Markov chain Monte Carlo (MCMC) algorithms for sampling from the posteiror and predictive distributions. The book presents a balance between theory and applications, and for each class of models discussed, detailed examples and analyses from case studies are presented whenever possible. The applications are all essentially from the health sciences, including cancer, AIDS, and the environment. The book is intended as a graduate textbook or a reference book for a one semester course at the advanced masters or Ph.D. level. This book would be most suitable for second or third year graduate students in statistics or biostatistics. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners | ||
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Datensatz im Suchindex
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any_adam_object | |
author | Ibrahim, Joseph G. |
author_facet | Ibrahim, Joseph G. |
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author_variant | j g i jg jgi |
building | Verbundindex |
bvnumber | BV042421472 |
classification_tum | MAT 000 |
collection | ZDB-2-SMA ZDB-2-BAE |
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dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.5 |
dewey-search | 519.5 |
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dewey-tens | 510 - Mathematics |
discipline | Mathematik |
doi_str_mv | 10.1007/978-1-4757-3447-8 |
format | Electronic eBook |
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id | DE-604.BV042421472 |
illustrated | Not Illustrated |
indexdate | 2024-12-20T17:10:44Z |
institution | BVB |
isbn | 9781475734478 9781441929334 |
issn | 0172-7397 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027856889 |
oclc_num | 863936964 |
open_access_boolean | |
owner | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
owner_facet | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
physical | 1 Online-Ressource (XIV, 480 p) |
psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
publishDate | 2001 |
publishDateSearch | 2001 |
publishDateSort | 2001 |
publisher | Springer New York |
record_format | marc |
series2 | Springer Series in Statistics |
spellingShingle | Ibrahim, Joseph G. Bayesian Survival Analysis Statistics Mathematical statistics Statistics for Life Sciences, Medicine, Health Sciences Statistical Theory and Methods Statistik Zuverlässigkeitstheorie (DE-588)4195525-0 gnd Bayes-Verfahren (DE-588)4204326-8 gnd Überlebenszeit (DE-588)4186609-5 gnd |
subject_GND | (DE-588)4195525-0 (DE-588)4204326-8 (DE-588)4186609-5 |
title | Bayesian Survival Analysis |
title_auth | Bayesian Survival Analysis |
title_exact_search | Bayesian Survival Analysis |
title_full | Bayesian Survival Analysis by Joseph G. Ibrahim, Ming-Hui Chen, Debajyoti Sinha |
title_fullStr | Bayesian Survival Analysis by Joseph G. Ibrahim, Ming-Hui Chen, Debajyoti Sinha |
title_full_unstemmed | Bayesian Survival Analysis by Joseph G. Ibrahim, Ming-Hui Chen, Debajyoti Sinha |
title_short | Bayesian Survival Analysis |
title_sort | bayesian survival analysis |
topic | Statistics Mathematical statistics Statistics for Life Sciences, Medicine, Health Sciences Statistical Theory and Methods Statistik Zuverlässigkeitstheorie (DE-588)4195525-0 gnd Bayes-Verfahren (DE-588)4204326-8 gnd Überlebenszeit (DE-588)4186609-5 gnd |
topic_facet | Statistics Mathematical statistics Statistics for Life Sciences, Medicine, Health Sciences Statistical Theory and Methods Statistik Zuverlässigkeitstheorie Bayes-Verfahren Überlebenszeit |
url | https://doi.org/10.1007/978-1-4757-3447-8 |
work_keys_str_mv | AT ibrahimjosephg bayesiansurvivalanalysis AT chenminghui bayesiansurvivalanalysis AT sinhadebajyoti bayesiansurvivalanalysis |