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EnglishThis paper presents a possible solution to the problem of identification of factors influencing long-term survival patients, using regression trees. The separation of the two classes of long-term survivors (cured patients) and of failed-to-cure patients is generalized to l* classes of survivors and is carried out via a latent variable, whose determinations are provided by the regression-tree classification. Two sets of factors are thus identified within the set of covariates: the factors influencing the prognosis and those influencing the survival classification (diagnostic factors). The relationship between the two sets is then explored, both theoretically and using an application to a data set of multiple myeloma patients. (C) 1998 John Wiley & Sons, Ltd.
Brambilla, C., Rossi, C., & Schinaia, G. (1997). Tree-structured analysis of survival data - Search for latent diagnostic factors in a tumour study. In Applied Stochastic Models and Data Analysis (pp.333-343). W SUSSEX : JOHN WILEY & SONS LTD.
| Autori: | ||
| Autori: | Brambilla, C; Rossi, C; Schinaia, G | |
| Titolo: | Tree-structured analysis of survival data - Search for latent diagnostic factors in a tumour study | |
| Nome del convegno: | 7th International Symposium on Applied Stochastic Models and Data Analysis | |
| Luogo del convegno: | DUBLIN, IRELAND | |
| Anno del convegno: | JUN 12-15, 1995 | |
| Rilevanza: | Rilevanza internazionale | |
| Sezione: | contributo | |
| Data di pubblicazione: | 1997 | |
| Settore Scientifico Disciplinare: | Settore MED/01 - Statistica Medica | |
| Lingua: | English | |
| Tipologia: | Intervento a convegno | |
| Citazione: | Brambilla, C., Rossi, C., & Schinaia, G. (1997). Tree-structured analysis of survival data - Search for latent diagnostic factors in a tumour study. In Applied Stochastic Models and Data Analysis (pp.333-343). W SUSSEX : JOHN WILEY & SONS LTD. | |
| Appare nelle tipologie: | 02 - Intervento a convegno |
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