Using data from multiple studies to develop a child growth correlation matrix

Anderson, C. , Xiao, L. and Checkley, W. (2019) Using data from multiple studies to develop a child growth correlation matrix. Statistics in Medicine, 30(19), pp. 3540-3554. (doi:10.1002/sim.7696) (PMID:29700850)

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Abstract

In many countries, the monitoring of child growth does not occur in a regular manner, and instead, we may have to rely on sporadic observations that are subject to substantial measurement error. In these countries, it can be difficult to identify patterns of poor growth, and faltering children may miss out on essential health interventions. The contribution of this paper is to provide a framework for pooling together multiple datasets, thus allowing us to overcome the issue of sparse data and provide improved estimates of growth. We use data from multiple longitudinal growth studies to construct a common correlation matrix that can be used in estimation and prediction of child growth. We propose a novel 2‐stage approach: In stage 1, we construct a raw matrix via a set of univariate meta‐analyses, and in stage 2, we smooth this raw matrix to obtain a more realistic correlation matrix. The methodology is illustrated using data from 16 child growth studies from the Bill and Melinda Gates Foundation's Healthy Birth Growth and Development knowledge integration project and identifies strong correlation for both height and weight between the ages of 4 and 12 years. We use a case study to provide an example of how this matrix can be used to help compute growth measures.

Item Type:Articles
Additional Information:The HBGDki initiative was supported by the Bill and Melinda Gates Foundation.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Anderson, Dr Craig
Authors: Anderson, C., Xiao, L., and Checkley, W.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Statistics in Medicine
Publisher:Wiley
ISSN:0277-6715
ISSN (Online):1097-0258
Published Online:27 April 2018
Copyright Holders:Copyright © 2018 The Authors
First Published:First published in Statistics in Medicine 38:3540-3554
Publisher Policy:Reproduced under a Creative Commons License

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