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自闭症研究中的大数据:方法学挑战与解决方案。

Big data in autism research: Methodological challenges and solutions.

机构信息

Department of Epidemiology and Biostatistics, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA.

Modifiable autism risk factors research program, A.J. Drexel Autism Institute, Philadelphia, Pennsylvania, USA.

出版信息

Autism Res. 2023 Oct;16(10):1852-1858. doi: 10.1002/aur.3007. Epub 2023 Aug 19.

Abstract

While the concept of big data has emerged over the past decade as a hot topic in nearly all areas of scientific inquiry, it has rarely been discussed in the context of autism research. In this commentary we describe aspects of big data that are relevant to autism research and methodological issues such as confounding and data error that can hamper scientific investigation. Although big data studies can have transformative impact, bigger is not always better, and big data require the same methodological considerations and interdisciplinary collaboration as "small data" to extract useful scientific insight.

摘要

虽然大数据的概念在过去十年中已经成为几乎所有科学研究领域的热门话题,但在自闭症研究中很少被提及。在这篇评论中,我们描述了与自闭症研究相关的大数据的各个方面,以及可能阻碍科学研究的混杂和数据错误等方法学问题。尽管大数据研究可能具有变革性的影响,但更大并不总是更好,而且大数据需要与“小数据”一样的方法学考虑和跨学科合作,以提取有用的科学见解。

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