Life course of retrospective harmonization initiatives: key elements to consider

Author:

Fortier IsabelORCID,Wey Tina W.,Bergeron Julie,Pinot de Moira Angela,Nybo-Andersen Anne-MarieORCID,Bishop Tom,Murtagh Madeleine J.,Miočević Milica,Swertz Morris A.,van Enckevort Esther,Marcon Yannick,Mayrhofer Michaela. Th.,Ornelas Jos Pedro,Sebert Sylvain,Santos Ana Cristina,Rocha Artur,Wilson Rebecca C.,Griffith Lauren E.,Burton Paul

Abstract

AbstractOptimizing research on the developmental origins of health and disease (DOHaD) involves implementing initiatives maximizing the use of the available cohort study data; achieving sufficient statistical power to support subgroup analysis; and using participant data presenting adequate follow-up and exposure heterogeneity. It also involves being able to undertake comparison, cross-validation, or replication across data sets. To answer these requirements, cohort study data need to be findable, accessible, interoperable, and reusable (FAIR), and more particularly, it often needs to be harmonized. Harmonization is required to achieve or improve comparability of the putatively equivalent measures collected by different studies on different individuals. Although the characteristics of the research initiatives generating and using harmonized data vary extensively, all are confronted by similar issues. Having to collate, understand, process, host, and co-analyze data from individual cohort studies is particularly challenging. The scientific success and timely management of projects can be facilitated by an ensemble of factors. The current document provides an overview of the ‘life course’ of research projects requiring harmonization of existing data and highlights key elements to be considered from the inception to the end of the project.

Publisher

Cambridge University Press (CUP)

Subject

Medicine (miscellaneous)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A General Primer for Data Harmonization;Scientific Data;2024-01-31

2. Harmonization for Cross‐National Secondary Analysis: Survey Data Recycling;Survey Data Harmonization in the Social Sciences;2023-11-10

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