Zhang, Wenyang, Steele, Fiona (2004) A semiparametric multilevel survival model. Journal of the Royal Statistical Society: Series C (Applied Statistics), 53 (Part 2). pp. 387-404. ISSN 0035-9254. (doi:10.1111/j.1467-9876.2003.05056.x) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:602)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1111/j.1467-9876.2003.05056.x |
Abstract
We propose a semiparametric multilevel survival model for clustered duration data in which the effect of a continuous covariate is represented by an unspecified, possibly non-linear, function. This model makes no distributional assumption about the cluster level random effects. The performance of the method is assessed via Monte Carlo simulations. The model is applied in an analysis of first-birth intervals in Bangladesh to examine period effects in the timing of first births, while allowing for clustering within communities; the analysis reveals a non-linear trend in the first-birth interval over time. This paper also proposed a novel
way to do ANOVA for curve data.
Item Type: | Article |
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DOI/Identification number: | 10.1111/j.1467-9876.2003.05056.x |
Uncontrolled keywords: | clustered data; first-birth interval; multilevel model; semiparametric survival model |
Subjects: | H Social Sciences > HA Statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Judith Broom |
Date Deposited: | 19 Dec 2007 18:22 UTC |
Last Modified: | 05 Nov 2024 09:30 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/602 (The current URI for this page, for reference purposes) |
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