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注册前协调数据分析的挑战与机遇：教程与模板。

Challenges and opportunities in preregistration of coordinated data analysis: A tutorial and template.

机构信息

Department of Medical Social Sciences.

出版信息

Psychol Aging. 2022 Feb;37(1):136-140. doi: 10.1037/pag0000611. Epub 2021 May 20.

DOI:10.1037/pag0000611
PMID:34014745
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8605032/
Abstract

The credibility revolution in social science has led to the recommendation and adoption of practices to increase the replicability of scientific findings. Many of the recommended practices, such as replication and preregistration, present unique challenges for aging research given its reliance on long-term longitudinal data. In this tutorial, we propose preregistered coordinated data analysis as a promising approach that involves both replication and preregistration, but that overcomes the aforementioned challenges by using existing data. We discuss the benefits of preregistering coordinated data analysis and provide an add-on template to be used in conjunction with existing preregistration templates for preregistering coordinated data analysis. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

摘要

社会科学中的可信度革命促使人们推荐和采用各种实践方法来提高科学发现的可重复性。鉴于老龄化研究依赖于长期纵向数据，许多推荐的实践方法（如复制和预先注册）都给该研究带来了独特的挑战。在本教程中，我们提出了预先注册的协调数据分析作为一种很有前途的方法，该方法既涉及复制，也涉及预先注册，但通过使用现有数据克服了上述挑战。我们讨论了预先注册协调数据分析的好处，并提供了一个附加模板，可与现有的预先注册模板一起用于预先注册协调数据分析。

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