Longitudinal Data Regression Analysis Using Semiparametric Modelling

Zhang, Leng and Tang (2015) propose joint parametric modelling of the means, variances, and the correlations by decomposing the correlation matrix via hyperspherical co-ordinates and show that this results unconstrained parameterization, fast computation, easy interpretation of the parameters, and...

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Main Authors: Abdulla Mamun, Sudhir Paul
Format: Article
Language:English
Published: Instituto Nacional de Estatística | Statistics Portugal 2025-08-01
Series:Revstat Statistical Journal
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Online Access:https://revstat.ine.pt/index.php/REVSTAT/article/view/580
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author Abdulla Mamun
Sudhir Paul
author_facet Abdulla Mamun
Sudhir Paul
author_sort Abdulla Mamun
collection DOAJ
description Zhang, Leng and Tang (2015) propose joint parametric modelling of the means, variances, and the correlations by decomposing the correlation matrix via hyperspherical co-ordinates and show that this results unconstrained parameterization, fast computation, easy interpretation of the parameters, and model parsimony. With unconstrained structures, they also suggest future research on modelling the mean, the variance, and the correlations non-parametrically and semiparametrically. In this paper we explore semiparametric modelling via simulations and data analysis. Extensive simulations show that the semiparametric modelling produces similar bias and efficiency properties of the parameter estimates as those by the parametric modelling. However, model selection, using the AIC and the BIC, through the analysis of two real biomedical data sets show significant improvement in model parsimony.
format Article
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institution Kabale University
issn 1645-6726
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language English
publishDate 2025-08-01
publisher Instituto Nacional de Estatística | Statistics Portugal
record_format Article
series Revstat Statistical Journal
spelling doaj-art-9b81cb3ff73646c8a48449aeff931d6b2025-08-20T03:37:54ZengInstituto Nacional de Estatística | Statistics PortugalRevstat Statistical Journal1645-67262183-03712025-08-01233Longitudinal Data Regression Analysis Using Semiparametric ModellingAbdulla Mamun0Sudhir Paul 1Gonzaga UniversityUniversity of Windsor Zhang, Leng and Tang (2015) propose joint parametric modelling of the means, variances, and the correlations by decomposing the correlation matrix via hyperspherical co-ordinates and show that this results unconstrained parameterization, fast computation, easy interpretation of the parameters, and model parsimony. With unconstrained structures, they also suggest future research on modelling the mean, the variance, and the correlations non-parametrically and semiparametrically. In this paper we explore semiparametric modelling via simulations and data analysis. Extensive simulations show that the semiparametric modelling produces similar bias and efficiency properties of the parameter estimates as those by the parametric modelling. However, model selection, using the AIC and the BIC, through the analysis of two real biomedical data sets show significant improvement in model parsimony. https://revstat.ine.pt/index.php/REVSTAT/article/view/580B-splinehyperspherical co-ordinatesjoint mean-covariance modelslongitudinal datamodel parsimonypenalized spline
spellingShingle Abdulla Mamun
Sudhir Paul
Longitudinal Data Regression Analysis Using Semiparametric Modelling
Revstat Statistical Journal
B-spline
hyperspherical co-ordinates
joint mean-covariance models
longitudinal data
model parsimony
penalized spline
title Longitudinal Data Regression Analysis Using Semiparametric Modelling
title_full Longitudinal Data Regression Analysis Using Semiparametric Modelling
title_fullStr Longitudinal Data Regression Analysis Using Semiparametric Modelling
title_full_unstemmed Longitudinal Data Regression Analysis Using Semiparametric Modelling
title_short Longitudinal Data Regression Analysis Using Semiparametric Modelling
title_sort longitudinal data regression analysis using semiparametric modelling
topic B-spline
hyperspherical co-ordinates
joint mean-covariance models
longitudinal data
model parsimony
penalized spline
url https://revstat.ine.pt/index.php/REVSTAT/article/view/580
work_keys_str_mv AT abdullamamun longitudinaldataregressionanalysisusingsemiparametricmodelling
AT sudhirpaul longitudinaldataregressionanalysisusingsemiparametricmodelling