| _version_ | 1867015479643602944 |
|---|---|
| author | Malka Gorfine Richard J. Cook Per Kragh Andersen Terry M. Therneau Pierre Joly Hein Putter Maja Pohar Perme Michal Abrahamowicz |
| author_facet | Malka Gorfine Richard J. Cook Per Kragh Andersen Terry M. Therneau Pierre Joly Hein Putter Maja Pohar Perme Michal Abrahamowicz Malka Gorfine Richard J. Cook Per Kragh Andersen Terry M. Therneau Pierre Joly Hein Putter Maja Pohar Perme Michal Abrahamowicz |
| collection | Wiley Open Access |
| contents | An Overview and Recent Developments in the Analysis of Multistate Processes Malka Gorfine Richard J. Cook Per Kragh Andersen Terry M. Therneau Pierre Joly Hein Putter Maja Pohar Perme Michal Abrahamowicz Statistics in Medicine ABSTRACT Multistate models offer a powerful framework for studying disease processes and can be used to formulate intensity‐based and more descriptive marginal regression models. They also represent a natural foundation for the construction of joint models for disease processes and dynamic marker processes, as well as joint models incorporating random censoring and intermittent observation times. This article reviews the ways multistate models can be formed and fitted to life history data. Recent work on pseudo‐values and the incorporation of random effects to model dependence on the process history and between‐process heterogeneity are also discussed. The software available to facilitate such analyses is listed. 10.1002/sim.70493 http://creativecommons.org/licenses/by/4.0/ |
| doi_str_mv | 10.1002/sim.70493 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_sim_70493 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| publishDate | 2026 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | An Overview and Recent Developments in the Analysis of Multistate Processes Malka Gorfine Richard J. Cook Per Kragh Andersen Terry M. Therneau Pierre Joly Hein Putter Maja Pohar Perme Michal Abrahamowicz Statistics in Medicine An Overview and Recent Developments in the Analysis of Multistate Processes Malka Gorfine Richard J. Cook Per Kragh Andersen Terry M. Therneau Pierre Joly Hein Putter Maja Pohar Perme Michal Abrahamowicz Statistics in Medicine ABSTRACT Multistate models offer a powerful framework for studying disease processes and can be used to formulate intensity‐based and more descriptive marginal regression models. They also represent a natural foundation for the construction of joint models for disease processes and dynamic marker processes, as well as joint models incorporating random censoring and intermittent observation times. This article reviews the ways multistate models can be formed and fitted to life history data. Recent work on pseudo‐values and the incorporation of random effects to model dependence on the process history and between‐process heterogeneity are also discussed. The software available to facilitate such analyses is listed. 10.1002/sim.70493 http://creativecommons.org/licenses/by/4.0/ |
| title | An Overview and Recent Developments in the Analysis of Multistate Processes |
| topic | Statistics in Medicine |
| url | https://onlinelibrary.wiley.com/doi/10.1002/sim.70493 |