Semiparametric Likelihood Estimation in the Clayton–Oakes Failure Time Model

Autor:	D. V. Glidden, S. G. Self
Rok vydání:	1999
Předmět:	Statistics and Probability Estimation Multivariate statistics Estimation theory Maximum likelihood Statistics Failure rate Time model Sample (statistics) Statistics Probability and Uncertainty Marginal distribution Mathematics
Zdroj:	Scandinavian Journal of Statistics. 26:363-372
ISSN:	1467-9469 0303-6898
DOI:	10.1111/1467-9469.00154
Popis:	Multivariate failure time data arise when the sample consists of clusters and each cluster contains several possibly dependent failure times. The Clayton-Oakes model (Clayton, 1978; Oakes, 1982) for multivariate failure times characterizes the intracluster dependence parametrically but allows arbitrary specification of the marginal distributions. In this paper, we discuss estimation in the Clayton-Oakes model when the marginal distributions are modeled to follow the Cox (1972) proportional hazards regression model. Parameter estimation is based on an approximate generalized maximum likelihood estima- tor. We illustrate the model's application with example datasets.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ca6ace619c9d61ddb23ccae0658972b3 https://doi.org/10.1111/1467-9469.00154 Zobrazit plný text záznamu Plný text ve formátu PDF