Selecting Covariance Structure to Analyze Longitudinal Data: A Study to Model the Body Mass Index of Primary School-Going Children in Bangladesh

Mohammad Ohid Ullah () and Mst. Farzana Akter ()
Additional contact information
Mohammad Ohid Ullah: Shahjalal University of Science and Technology, Department of Statistics
Mst. Farzana Akter: Shahjalal University of Science and Technology, Department of Statistics

A chapter in Data Science and SDGs, 2021, pp 147-153 from Springer

Abstract: Abstract In the longitudinal study, the data are collected from the same subject over time and hence the data are correlated. To analyze such data selecting an efficient covariance structure is very important to get better results. Therefore, this article is aimed to select an efficient covariance structure to model the body mass index (BMI) of primary school-going children in Bangladesh. In this study, at first, we have conducted a longitudinal survey to build a cohort of 100 primary school-going children in Sylhet city, Bangladesh. We collected the information from the same children at the initial time (T0), after 6 months (T6), after 12 months (T12) and after 18 months (T18). Linear mixed model (LMM) is applied for selecting an efficient covariance structure and then to model the body mass index. To find out a better covariance structure, we used diagonal, unstructured (UN), auto Regressive order 1 (AR1) and compound symmetry (CS) covariance structures in collecting longitudinal data. Observing all the criteria, it is found that the covariance structure compound symmetry (‘CS’) gives better results for LMM. Finally using the CS covariance structure, initially, we observed that the BMI of male students’ is comparatively smaller than female students’ (Estimate = -−.04, P-value = 0.03). But overtime, a reverse result is observed at T12 and T18. Taken together, we may conclude that compound symmetry (CS) gives better output to model the body mass index of primary school-going children. As female students are getting more obese, in addition, today’s female children are the mothers of the future. Therefore, parents should give concentration to female children to reduce their body weight. This study may be useful for researchers in public health sectors to select a proper covariance structure to analyze their longitudinal data.

Keywords: Compound symmetry; Obesity; Longitudinal study; Linear mixed model; Public health (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-16-1919-9_12

Ordering information: This item can be ordered from
http://www.springer.com/9789811619199

DOI: 10.1007/978-981-16-1919-9_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().