Murdoch Childrens Research Institute
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LifeCourse_Open_Code_Resource_V1_20240520.pdf (445.53 kB)

Open Code: Promoting Efficiency and Reproducibility of LifeCourse Analyses

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posted on 2024-05-20, 07:17 authored by Meredith O'ConnorMeredith O'Connor

LifeCourse is a collaborative of more than 20 longitudinal cohort studies. We help researchers to discover, access, and use these rich data to undertake new and impactful research that benefits health over the life span. Analyses of LifeCourse cohorts are inherently complex, requiring extensive manipulation of data and sophisticated modelling, executed within Stata, R, or other statistical programming languages. Sharing of the code underpinning a paper’s analysis promotes transparency and reproducibility of the study’s conclusions. It is also efficient, allowing future data users to build on work already undertaken. By sharing analytic code, researchers can maximise the value of their research, gain visibility and citations, publish in the increasing number of journals where this is a requirement, and foster an environment of open science and collaborative research. This resource highlights some of the key considerations in sharing code to maximise these benefits for cohort researchers. 

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