Analysis of Multivariate Survival Data:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
2000
|
| Schriftenreihe: | Statistics for Biology and Health
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariate times. Applications where such data appear are survival of twins, survival of married couples and families, time to failure of right and left kidney for diabetic patients, life history data with time to outbreak of disease, complications and death, recurrent episodes of diseases and cross-over studies with time responses. As the field is rather new, the concepts and the possible types of data are described in detail and basic aspects of how dependence can appear in such data is discussed. Four different approaches to the analysis of such data are presented. The multi-state models where a life history is described as the subject moving from state to state is the most classical approach. The Markov models make up an important special case, but it is also described how easily more general models are set up and analyzed. Frailty models, which are random effects models for survival data, made a second approach, extending from the most simple shared frailty models, which are considered in detail, to models with more complicated dependence structures over individuals or over time. Marginal modelling has become a popular approach to evaluate the effect of explanatory factors in the presence of dependence, but without having specified a statistical model for the dependence. Finally, the completely non-parametric approach to bivariate censored survival data is described. This book is aimed at investigators who need to analyze multivariate survival data, but due to its focus on the concepts and the modelling aspects, it is also useful for persons interested in such data, but |
| Beschreibung: | 1 Online-Ressource (XVII, 542 p) |
| ISBN: | 9781461213048 9781461270874 |
| ISSN: | 1431-8776 |
| DOI: | 10.1007/978-1-4612-1304-8 |
Internformat
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Datensatz im Suchindex
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| author | Hougaard, Philip |
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| author_variant | p h ph |
| building | Verbundindex |
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| classification_tum | MAT 000 |
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| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4612-1304-8 |
| format | Electronic eBook |
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| id | DE-604.BV042419796 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:05Z |
| institution | BVB |
| isbn | 9781461213048 9781461270874 |
| issn | 1431-8776 |
| language | English |
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| spelling | Hougaard, Philip Verfasser aut Analysis of Multivariate Survival Data by Philip Hougaard New York, NY Springer New York 2000 1 Online-Ressource (XVII, 542 p) txt rdacontent c rdamedia cr rdacarrier Statistics for Biology and Health 1431-8776 Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariate times. Applications where such data appear are survival of twins, survival of married couples and families, time to failure of right and left kidney for diabetic patients, life history data with time to outbreak of disease, complications and death, recurrent episodes of diseases and cross-over studies with time responses. As the field is rather new, the concepts and the possible types of data are described in detail and basic aspects of how dependence can appear in such data is discussed. Four different approaches to the analysis of such data are presented. The multi-state models where a life history is described as the subject moving from state to state is the most classical approach. The Markov models make up an important special case, but it is also described how easily more general models are set up and analyzed. Frailty models, which are random effects models for survival data, made a second approach, extending from the most simple shared frailty models, which are considered in detail, to models with more complicated dependence structures over individuals or over time. Marginal modelling has become a popular approach to evaluate the effect of explanatory factors in the presence of dependence, but without having specified a statistical model for the dependence. Finally, the completely non-parametric approach to bivariate censored survival data is described. This book is aimed at investigators who need to analyze multivariate survival data, but due to its focus on the concepts and the modelling aspects, it is also useful for persons interested in such data, but Statistics Medicine Statistics for Life Sciences, Medicine, Health Sciences Medicine/Public Health, general Medizin Statistik Ereignisdatenanalyse (DE-588)4132103-0 gnd rswk-swf Medizinische Statistik (DE-588)4127563-9 gnd rswk-swf Multivariate Daten (DE-588)4195680-1 gnd rswk-swf Überleben (DE-588)4117273-5 gnd rswk-swf Überleben (DE-588)4117273-5 s Multivariate Daten (DE-588)4195680-1 s Medizinische Statistik (DE-588)4127563-9 s 1\p DE-604 Ereignisdatenanalyse (DE-588)4132103-0 s 2\p DE-604 https://doi.org/10.1007/978-1-4612-1304-8 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Hougaard, Philip Analysis of Multivariate Survival Data Statistics Medicine Statistics for Life Sciences, Medicine, Health Sciences Medicine/Public Health, general Medizin Statistik Ereignisdatenanalyse (DE-588)4132103-0 gnd Medizinische Statistik (DE-588)4127563-9 gnd Multivariate Daten (DE-588)4195680-1 gnd Überleben (DE-588)4117273-5 gnd |
| subject_GND | (DE-588)4132103-0 (DE-588)4127563-9 (DE-588)4195680-1 (DE-588)4117273-5 |
| title | Analysis of Multivariate Survival Data |
| title_auth | Analysis of Multivariate Survival Data |
| title_exact_search | Analysis of Multivariate Survival Data |
| title_full | Analysis of Multivariate Survival Data by Philip Hougaard |
| title_fullStr | Analysis of Multivariate Survival Data by Philip Hougaard |
| title_full_unstemmed | Analysis of Multivariate Survival Data by Philip Hougaard |
| title_short | Analysis of Multivariate Survival Data |
| title_sort | analysis of multivariate survival data |
| topic | Statistics Medicine Statistics for Life Sciences, Medicine, Health Sciences Medicine/Public Health, general Medizin Statistik Ereignisdatenanalyse (DE-588)4132103-0 gnd Medizinische Statistik (DE-588)4127563-9 gnd Multivariate Daten (DE-588)4195680-1 gnd Überleben (DE-588)4117273-5 gnd |
| topic_facet | Statistics Medicine Statistics for Life Sciences, Medicine, Health Sciences Medicine/Public Health, general Medizin Statistik Ereignisdatenanalyse Medizinische Statistik Multivariate Daten Überleben |
| url | https://doi.org/10.1007/978-1-4612-1304-8 |
| work_keys_str_mv | AT hougaardphilip analysisofmultivariatesurvivaldata |