Semiparametric binary model for clustered survival data

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...

Full description

Bibliographic Details
Main Authors: Arlin, Rifina, Ibrahim, Noor Akma, Arasan, Jayanthi, Abu Bakar, Mohd Rizam
Format: Conference or Workshop Item
Language:English
Published: AIP Publishing LLC 2014
Online Access:http://psasir.upm.edu.my/id/eprint/57347/1/Semiparametric%20binary%20model%20for%20clustered%20survival%20data.pdf
_version_ 1825931594562535424
author Arlin, Rifina
Ibrahim, Noor Akma
Arasan, Jayanthi
Abu Bakar, Mohd Rizam
author_facet Arlin, Rifina
Ibrahim, Noor Akma
Arasan, Jayanthi
Abu Bakar, Mohd Rizam
author_sort Arlin, Rifina
collection UPM
description 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.
first_indexed 2024-03-06T09:29:06Z
format Conference or Workshop Item
id upm.eprints-57347
institution Universiti Putra Malaysia
language English
last_indexed 2024-03-06T09:29:06Z
publishDate 2014
publisher AIP Publishing LLC
record_format dspace
spelling upm.eprints-573472017-09-26T04:10:06Z http://psasir.upm.edu.my/id/eprint/57347/ Semiparametric binary model for clustered survival data Arlin, Rifina Ibrahim, Noor Akma Arasan, Jayanthi Abu Bakar, Mohd Rizam 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. AIP Publishing LLC 2014 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/57347/1/Semiparametric%20binary%20model%20for%20clustered%20survival%20data.pdf 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. . 10.1063/1.4932507
spellingShingle Arlin, Rifina
Ibrahim, Noor Akma
Arasan, Jayanthi
Abu Bakar, Mohd Rizam
Semiparametric binary model for clustered survival data
title Semiparametric binary model for clustered survival data
title_full Semiparametric binary model for clustered survival data
title_fullStr Semiparametric binary model for clustered survival data
title_full_unstemmed Semiparametric binary model for clustered survival data
title_short Semiparametric binary model for clustered survival data
title_sort semiparametric binary model for clustered survival data
url http://psasir.upm.edu.my/id/eprint/57347/1/Semiparametric%20binary%20model%20for%20clustered%20survival%20data.pdf
work_keys_str_mv AT arlinrifina semiparametricbinarymodelforclusteredsurvivaldata
AT ibrahimnoorakma semiparametricbinarymodelforclusteredsurvivaldata
AT arasanjayanthi semiparametricbinarymodelforclusteredsurvivaldata
AT abubakarmohdrizam semiparametricbinarymodelforclusteredsurvivaldata