|
Registro Completo |
|
Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
|
Data corrente: |
29/08/1995 |
|
Data da última atualização: |
29/08/1995 |
|
Autoria: |
BENNETT, S/. |
|
Afiliação: |
Department of Applied Statistics, University of Reading, Whiteknights, Reading, RG6 2AN UK. |
|
Título: |
Log-logistic regression models for survival data. |
|
Ano de publicação: |
1983 |
|
Fonte/Imprenta: |
Appl. Statist., v.32, n.2, p.165-171, 1983. |
|
Idioma: |
Inglês |
|
Conteúdo: |
The log-logistic distribution has a no-monotonic hazard function which makes it suitable for modelling some sets of cancer survival data. A log-logistic regression model is described in which the hazard functions for separate separate samples coverge with time. This also provides a linear model for the log odds on survival by any chosen time. The model is fitted on GLIM and an example is given of its use with lung cancer survival data. |
|
Palavras-Chave: |
Glim; Hazard rate; Linear logistic model; Log-logistic distribution; Survival data. |
|
Thesaurus Nal: |
odds ratio. |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 00939naa a2200193 a 4500
001 1646911
005 1995-08-29
008 1983 bl --- 0-- u #d
100 1 $aBENNETT, S/
245 $aLog-logistic regression models for survival data.
260 $c1983
520 $aThe log-logistic distribution has a no-monotonic hazard function which makes it suitable for modelling some sets of cancer survival data. A log-logistic regression model is described in which the hazard functions for separate separate samples coverge with time. This also provides a linear model for the log odds on survival by any chosen time. The model is fitted on GLIM and an example is given of its use with lung cancer survival data.
650 $aodds ratio
653 $aGlim
653 $aHazard rate
653 $aLinear logistic model
653 $aLog-logistic distribution
653 $aSurvival data
773 $tAppl. Statist.$gv.32, n.2, p.165-171, 1983.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Mandioca e Fruticultura (CNPMF) |
