mstate: An R Package for the Analysis of Competing Risks and Multi-State Models
Multi-state models are a very useful tool to answer a wide range of questions in survival analysis that cannot, or only in a more complicated way, be answered by classical models. They are suitable for both biomedical and other applications in which time-to-event variables are analyzed. However, the...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Foundation for Open Access Statistics
2011-01-01
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| Series: | Journal of Statistical Software |
| Subjects: | |
| Online Access: | http://www.jstatsoft.org/v38/i07/paper |
| _version_ | 1818960618553606144 |
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| author | Liesbeth C. de Wreede MArta Fiocco Hein Putter |
| author_facet | Liesbeth C. de Wreede MArta Fiocco Hein Putter |
| author_sort | Liesbeth C. de Wreede |
| collection | DOAJ |
| description | Multi-state models are a very useful tool to answer a wide range of questions in survival analysis that cannot, or only in a more complicated way, be answered by classical models. They are suitable for both biomedical and other applications in which time-to-event variables are analyzed. However, they are still not frequently applied. So far, an important reason for this has been the lack of available software. To overcome this problem, we have developed the mstate package in R for the analysis of multi-state models. The package covers all steps of the analysis of multi-state models, from model building and data preparation to estimation and graphical representation of the results. It can be applied to non- and semi-parametric (Cox) models. The package is also suitable for competing risks models, as they are a special category of multi-state models.This article offers guidelines for the actual use of the software by means of an elaborate multi-state analysis of data describing post-transplant events of patients with blood cancer. The data have been provided by the EBMT (the European Group for Blood and Marrow Transplantation). Special attention will be paid to the modeling of different covariate effects (the same for all transitions or transition-specific) and different baseline hazard assumptions (different for all transitions or equal for some). |
| first_indexed | 2024-12-20T12:00:24Z |
| format | Article |
| id | doaj.art-745e520696154f68ae1a2fe8e54a8d63 |
| institution | Directory Open Access Journal |
| issn | 1548-7660 |
| language | English |
| last_indexed | 2024-12-20T12:00:24Z |
| publishDate | 2011-01-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj.art-745e520696154f68ae1a2fe8e54a8d632022-12-21T19:41:34ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602011-01-013807mstate: An R Package for the Analysis of Competing Risks and Multi-State ModelsLiesbeth C. de WreedeMArta FioccoHein PutterMulti-state models are a very useful tool to answer a wide range of questions in survival analysis that cannot, or only in a more complicated way, be answered by classical models. They are suitable for both biomedical and other applications in which time-to-event variables are analyzed. However, they are still not frequently applied. So far, an important reason for this has been the lack of available software. To overcome this problem, we have developed the mstate package in R for the analysis of multi-state models. The package covers all steps of the analysis of multi-state models, from model building and data preparation to estimation and graphical representation of the results. It can be applied to non- and semi-parametric (Cox) models. The package is also suitable for competing risks models, as they are a special category of multi-state models.This article offers guidelines for the actual use of the software by means of an elaborate multi-state analysis of data describing post-transplant events of patients with blood cancer. The data have been provided by the EBMT (the European Group for Blood and Marrow Transplantation). Special attention will be paid to the modeling of different covariate effects (the same for all transitions or transition-specific) and different baseline hazard assumptions (different for all transitions or equal for some).http://www.jstatsoft.org/v38/i07/papercompeting risksestimationmulti-state modelspredictionRsurvival analysis |
| spellingShingle | Liesbeth C. de Wreede MArta Fiocco Hein Putter mstate: An R Package for the Analysis of Competing Risks and Multi-State Models Journal of Statistical Software competing risks estimation multi-state models prediction R survival analysis |
| title | mstate: An R Package for the Analysis of Competing Risks and Multi-State Models |
| title_full | mstate: An R Package for the Analysis of Competing Risks and Multi-State Models |
| title_fullStr | mstate: An R Package for the Analysis of Competing Risks and Multi-State Models |
| title_full_unstemmed | mstate: An R Package for the Analysis of Competing Risks and Multi-State Models |
| title_short | mstate: An R Package for the Analysis of Competing Risks and Multi-State Models |
| title_sort | mstate an r package for the analysis of competing risks and multi state models |
| topic | competing risks estimation multi-state models prediction R survival analysis |
| url | http://www.jstatsoft.org/v38/i07/paper |
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