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DC Field | Value | Language |
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dc.contributor.author | Al-Hamzawi, R | - |
dc.contributor.author | Yu, K | - |
dc.contributor.author | Pan, J | - |
dc.date.accessioned | 2013-02-08T16:32:05Z | - |
dc.date.available | 2013-02-08T16:32:05Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Journal of Biometrics and Biostatistics, 2: 115, Sep 2011 | en_US |
dc.identifier.issn | 2155-6180 | - |
dc.identifier.uri | http://www.omicsonline.org/2155-6180/2155-6180-2-115.php | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/7218 | - |
dc.description | © 2011 Alhamzawi R, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original auhor and source are credited. | en_US |
dc.description | This article has been made available through the Brunel Open Access Publishing Fund. | - |
dc.description.abstract | In this paper, we introduce Bayesian quantile regression for longitudinal data in terms of informative priors and Gibbs sampling. We develop methods for eliciting prior distribution to incorporate historical data gathered from similar previous studies. The methods can be used either with no prior data or with complete prior data. The advantage of the methods is that the prior distribution is changing automatically when we change the quantile. We propose Gibbs sampling methods which are computationally efficient and easy to implement. The methods are illustrated with both simulation and real data. | en_US |
dc.description.sponsorship | This article is made available through the Brunel Open Access Publishing Fund. | en_US |
dc.language.iso | en | en_US |
dc.publisher | OMICS Group | en_US |
dc.subject | Bayesian quantile regression | en_US |
dc.subject | Conditional distribution | en_US |
dc.subject | Gibbs sampling | en_US |
dc.subject | Longitudinal data | en_US |
dc.subject | Mixture representation | en_US |
dc.subject | Random effect | en_US |
dc.title | Prior elicitation in Bayesian quantile regression for longitudinal data | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.4172/2155-6180.1000115 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Active Staff | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths/Maths | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute for Ageing Studies | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Centre for the Analysis of Risk and Optimisation Modelling Applications | - |
Appears in Collections: | Publications Brunel OA Publishing Fund Dept of Mathematics Research Papers Mathematical Sciences |
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File | Description | Size | Format | |
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Fulltext.pdf | 1.71 MB | Adobe PDF | View/Open |
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