Generalized Logit-Based Proportional Hazards Models and Their Applications in Survival and Reliability Analyses

N. Balakrishnan (), M. C. Pardo and M. L. Avendaño
Additional contact information
N. Balakrishnan: McMaster University
M. C. Pardo: Faculty of Mathematics, Complutense University of Madrid
M. L. Avendaño: Faculty of Mathematics, Complutense University of Madrid

A chapter in Stochastic Reliability and Maintenance Modeling, 2013, pp 1-16 from Springer

Abstract: Abstract We introduce a flexible family of generalized logit-based regression models for survival and reliability analyses. We present its parametric as well as its semiparametric versions. The method of maximum likelihood and the partial likelihood approach are applied to estimate the parameters of the parametric and semiparametric models, respectively. This new family of models is illustrated with male laryngeal cancer data and compared with Cox regression.

Keywords: Survival analysis; Reliability analysis; Proportional hazards; Type-I generalized logistic distribution; Parametric and semiparametric models; Profile likelihood. (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-1-4471-4971-2_1

Ordering information: This item can be ordered from
http://www.springer.com/9781447149712

DOI: 10.1007/978-1-4471-4971-2_1

Access Statistics for this chapter

More chapters in Springer Series in Reliability Engineering from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().