Psychology researchers are rapidly adopting open science practices, yet clear guidelines on how to apply these practices to meta-analysis remain lacking. In this tutorial, we describe why open science is important in the context of meta-analysis in psychology, and suggest how to adopt the 3 main components of open science: preregistration, open materials, and open data. We first describe how to make the preregistration as thorough as possible—and how to handle deviations from the plan. We then focus on creating easy-to-read materials (e.g., search syntax, R scripts) to facilitate reproducibility and bolster the impact of a meta-analysis. Finally, we suggest how to organize data (e.g., literature search results, data extracted from studies) that are easy to share, interpret, and update as new studies emerge. For each step of the meta-analysis, we provide example templates, accompanied by brief video tutorials, and show how to integrate these practices into the Open Science Framework (https://osf.io/q8stz/). (PsycInfo Database Record (c) 2020 APA, all rights reserved)

中文翻译：

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在开放科学时代进行荟萃分析：工具、技巧和实用建议。

心理学研究人员正在迅速采用开放的科学实践，但仍然缺乏关于如何将这些实践应用于荟萃分析的明确指导方针。在本教程中，我们描述了为什么开放科学在心理学元分析的背景下很重要，并建议如何采用开放科学的 3 个主要组成部分：预注册、开放材料和开放数据。我们首先描述如何使预注册尽可能彻底，以及如何处理与计划的偏差。然后，我们专注于创建易于阅读的材料（例如，搜索语法、R 脚本）以促进可重复性并增强荟萃分析的影响。最后，我们建议如何组织数据（例如，文献检索结果、从研究中提取的数据），以便在新研究出现时易于共享、解释和更新。对于荟萃分析的每一步，我们提供了示例模板，并附有简短的视频教程，并展示了如何将这些实践集成到开放科学框架 (https://osf.io/q8stz/) 中。（PsycInfo 数据库记录 (c) 2020 APA，保留所有权利）