2026-06-26T16:04:19Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/244032023-08-10T22:15:33Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Avendano, M.L.
author
Pardo Llorente, María del Carmen
2023-06-18T06:51:11Z
2023-06-18T06:51:11Z
2016
0020-3157
10.1007/s10463-014-0496-3
https://hdl.handle.net/20.500.14352/24403
http://link.springer.com/article/10.1007/s10463-014-0496-3
http://www.springer.com/
We introduce a flexible family of semiparametric generalized logit-based regression models for survival analysis. Its hazard rates are proportional as the Cox model, but its relative risk related to a covariate is different for the values of the other covariates. The method of partial likelihood approach is applied to estimate its parameters in presence of right censoring and its asymptotic normality is established. We perform a simulation study to evaluate the finite-sample performance of these estimators. This new family of models is illustrated with lung cancer data and compared with Cox model. The importance of the conclusions obtained from the relative risk is pointed out.
eng
A semiparametric generalized proportional hazards model for right-censored data
journal article
URL
https://docta.ucm.es/bitstreams/ddc215b0-37bf-4246-bf0c-e902742f1fed/download
File
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936846
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art%3A10.1007%2Fs10463-014-0496-3.pdf