Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/79140
Título: | survidm: An R package for Inference and Prediction in an Illness-Death Model |
Autor(es): | Soutinho, Gustavo Sestelo, Marta Machado, Luís Meira |
Palavras-chave: | multistate model illness-death multistate regression transition probabilities |
Data: | 2021 |
Editora: | R Foundation for Statistical Computing |
Revista: | The R Journal |
Citação: | Soutinho, G., Sestelo, M., & Meira-Machado, L. (2021). survidm: An R package for Inference and Prediction in an Illness-Death Model. The R Journal. The R Foundation. http://doi.org/10.32614/rj-2021-070 |
Resumo(s): | Multi-state models are a useful way of describing a process in which an individual moves through a number of finite states in continuous time. The illness-death model plays a central role in the theory and practice of these models, describing the dynamics of healthy subjects who may move to an intermediate "diseased" state before entering into a terminal absorbing state. In these models, one important goal is the modeling of transition rates which is usually done by studying the relationship between covariates and disease evolution. However, biomedical researchers are also interested in reporting other interpretable results in a simple and summarized manner. These include estimates of predictive probabilities, such as the transition probabilities, occupation probabilities, cumulative incidence functions, and the sojourn time distributions. The development of survidm package has been motivated by recent contribution that provides answers to all these topics. An illustration of the software usage is included using real data. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/79140 |
DOI: | 10.32614/RJ-2021-070 |
ISSN: | 2073-4859 |
Versão da editora: | https://journal.r-project.org/archive/2021/RJ-2021-070/index.html |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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RJ-2021-070.pdf | Full Paper | 405,25 kB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons