Analysis of longitudinal data on child development using trivariate linear mixed models derived from copulas

Authors

DOI:

https://doi.org/10.5902/2179460X70316

Keywords:

Copulas, Longitudinal data, Children's anthropometric indices, Linear mixed models

Abstract

Longitudinal studies are quite common in the area of public health and, consequently, adequate statistical methods are required to analyze the temporal evolution of one or more response variables, separately or simultaneously. Specifying the joint density function of all response variables, as well as their correlation structure, are the main obstacles of multivariate modeling procedures. It is also important to highlight the numerical difficulties often encountered in statistical inference when the response dimension increases. As an alternative, this work presents two proposals to deal with multivariate longitudinal data: (i) a univariate approach, with linear mixed models fitted to each of the response variables separately; and (ii) a joint modeling of these variables, through the use of copula functions. Both methodologies are applied to a set of real trivariate data referring to the nutritional development of children in a Brazilian municipality in the state of Bahia.

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Author Biographies

Alexandro Oliveira, Universidade Federal da Bahia

Bachelor in Statistics (2013) and Master in Mathematics (with a concentration in Statistics) (2018) from the Federal University of Bahia (UFBA).

Ana Claudia Batista, Universidade Federal da Bahia

Bachelor in Statistics (2014) and Master in Mathematics (with a concentration in Statistics) (2019) from UFBA.

Marisleane Oliveira, Universidade Federal da Bahia

Bachelor in Statistics (2010) and Master in Mathematics (with a concentration in Statistics) (2019) from UFBA.

Paulo Henrique Ferreira, Universidade Federal da Bahia

Bachelor's (2009), Master's (2011) and Doctorate (2015) in Statistics from the Federal University of São Carlos (UFSCar). Post-Doctorate (2020) in Statistics from the Institute of Mathematical and Computer Sciences of the University of São Paulo (ICMC-USP).

Rosemeire Fiaccone, Universidade Federal da Bahia

PhD in Statistics from Lancaster University, UK, in 2006.

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Published

2024-12-19

How to Cite

Oliveira, A., Batista, A. C., Oliveira, M., Ferreira, P. H., & Fiaccone, R. (2024). Analysis of longitudinal data on child development using trivariate linear mixed models derived from copulas. Ciência E Natura, 46. https://doi.org/10.5902/2179460X70316

Issue

Vol. 46 (2024): Publicação contínua

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Statistics

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