Semiparametric binary model for clustered survival data

Citation

Arlin, Rifina and Ibrahim, Noor Akma and Arasan, Jayanthi and Abu Bakar, Mohd Rizam (2014) Semiparametric binary model for clustered survival data. In: 22nd National Symposium on Mathematical Sciences (SKSM22), 24-26 Nov. 2014, Grand Bluewave Hotel, Selangor. .

Abstract

This paper considers a method to analyze semiparametric binary models for clustered survival data when the responses are correlated. We extend parametric generalized estimating equation (GEE) to semiparametric GEE by introducing smoothing spline into the model. A backfitting algorithm is used in the derivation of the estimating equation for the parametric and nonparametric components of a semiparametric binary covariate model. The properties of the estimates for both are evaluated using simulation studies. We investigated the effects of the strength of cluster correlation and censoring rates on properties of the parameters estimate. The effect of the number of clusters and cluster size are also discussed. Results show that the GEE-SS are consistent and efficient for parametric component and nonparametric component of semiparametric binary covariates.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Science Institute for Mathematical Research
DOI Number:	https://doi.org/10.1063/1.4932507
Publisher:	AIP Publishing LLC
Keywords:	Clustered survival data; Generalized estimated equation; Simulation; Smoothing spline
Depositing User:	Nabilah Mustapa
Date Deposited:	26 Sep 2017 04:10
Last Modified:	26 Sep 2017 04:10
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1063/1.4932507
URI:	http://psasir.upm.edu.my/id/eprint/57347
Statistic Details:	View Download Statistic

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