First hitting time regression models: lifetime data analysis based on underlying stochastic processes
This book aims to promote regression methods for analyzing lifetime (or time-to-event) data that are based on a representation of the underlying process, and are therefore likely to offer greater scientific insight compared to purely empirical methods. In contrast to the rich statistical literature,...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London, UK
ISTE, Ltd.
2017
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| Schriftenreihe: | Mathematical models and methods in reliability set
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| Schlagworte: | |
| Online-Zugang: | FRO01 UBG01 Volltext |
| Zusammenfassung: | This book aims to promote regression methods for analyzing lifetime (or time-to-event) data that are based on a representation of the underlying process, and are therefore likely to offer greater scientific insight compared to purely empirical methods. In contrast to the rich statistical literature, the regression methods actually employed in lifetime data analysis are limited, particularly in the biomedical field where D. R. Cox{u2019}s famous semi-parametric proportional hazards model predominates. Practitioners should become familiar with more flexible models. The first hitting time regression models (or threshold regression) presented here represent observed events as the outcome of an underlying stochastic process. One example is death occurring when the patient{u2019}s health status falls to zero, but the idea has wide applicability {u2013} in biology, engineering, banking and finance, and elsewhere. The central topic is the model based on an underlying Wiener process, leading to lifetimes following the inverse Gaussian distribution. Introducing time-varying covariates and many other extensions are considered. Various applications are presented in detail.--Publisher's description |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9781119437260 9781119437222 |
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Datensatz im Suchindex
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| dewey-sort | 3519.5 236 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| format | Electronic eBook |
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| id | DE-604.BV044641958 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:58:00Z |
| institution | BVB |
| isbn | 9781119437260 9781119437222 |
| language | English |
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| oclc_num | 1012722490 |
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| publisher | ISTE, Ltd. |
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| series2 | Mathematical models and methods in reliability set |
| spelling | Caroni, Chrysseis Verfasser aut First hitting time regression models lifetime data analysis based on underlying stochastic processes Chrysseis Caroni London, UK ISTE, Ltd. 2017 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Mathematical models and methods in reliability set Includes bibliographical references and index This book aims to promote regression methods for analyzing lifetime (or time-to-event) data that are based on a representation of the underlying process, and are therefore likely to offer greater scientific insight compared to purely empirical methods. In contrast to the rich statistical literature, the regression methods actually employed in lifetime data analysis are limited, particularly in the biomedical field where D. R. Cox{u2019}s famous semi-parametric proportional hazards model predominates. Practitioners should become familiar with more flexible models. The first hitting time regression models (or threshold regression) presented here represent observed events as the outcome of an underlying stochastic process. One example is death occurring when the patient{u2019}s health status falls to zero, but the idea has wide applicability {u2013} in biology, engineering, banking and finance, and elsewhere. The central topic is the model based on an underlying Wiener process, leading to lifetimes following the inverse Gaussian distribution. Introducing time-varying covariates and many other extensions are considered. Various applications are presented in detail.--Publisher's description MATHEMATICS / Applied / bisacsh MATHEMATICS / Probability & Statistics / General / bisacsh Regression analysis / fast / (OCoLC)fst01432090 Stochastic processes / fast / (OCoLC)fst01133519 Regression analysis Stochastic processes https://onlinelibrary.wiley.com/doi/book/10.1002/10.1002/9781119437260 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Caroni, Chrysseis First hitting time regression models lifetime data analysis based on underlying stochastic processes MATHEMATICS / Applied / bisacsh MATHEMATICS / Probability & Statistics / General / bisacsh Regression analysis / fast / (OCoLC)fst01432090 Stochastic processes / fast / (OCoLC)fst01133519 Regression analysis Stochastic processes |
| title | First hitting time regression models lifetime data analysis based on underlying stochastic processes |
| title_auth | First hitting time regression models lifetime data analysis based on underlying stochastic processes |
| title_exact_search | First hitting time regression models lifetime data analysis based on underlying stochastic processes |
| title_full | First hitting time regression models lifetime data analysis based on underlying stochastic processes Chrysseis Caroni |
| title_fullStr | First hitting time regression models lifetime data analysis based on underlying stochastic processes Chrysseis Caroni |
| title_full_unstemmed | First hitting time regression models lifetime data analysis based on underlying stochastic processes Chrysseis Caroni |
| title_short | First hitting time regression models |
| title_sort | first hitting time regression models lifetime data analysis based on underlying stochastic processes |
| title_sub | lifetime data analysis based on underlying stochastic processes |
| topic | MATHEMATICS / Applied / bisacsh MATHEMATICS / Probability & Statistics / General / bisacsh Regression analysis / fast / (OCoLC)fst01432090 Stochastic processes / fast / (OCoLC)fst01133519 Regression analysis Stochastic processes |
| topic_facet | MATHEMATICS / Applied / bisacsh MATHEMATICS / Probability & Statistics / General / bisacsh Regression analysis / fast / (OCoLC)fst01432090 Stochastic processes / fast / (OCoLC)fst01133519 Regression analysis Stochastic processes |
| url | https://onlinelibrary.wiley.com/doi/book/10.1002/10.1002/9781119437260 |
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