Meta-analytic reviews are a primary avenue for the generation of cumulative knowledge in the organizational and psychological sciences. Over the past decade or two, concern has been raised about the possibility of publication bias influencing meta-analytic results, which can distort our cumulative knowledge and lead to erroneous practical recommendations. Unfortunately, no clear guidelines exist for how meta-analysts ought to assess this bias. To address this issue, this paper develops a user’s guide with best-practice recommendations for the assessment of publication bias in meta-analytic reviews. To do this, we review the literature on publication bias and develop a step-by-step process to assess the presence of publication bias and gage its effects on meta-analytic results. Examples of tools and best practices are provided to aid meta-analysts when implementing the process in their own research. Although the paper is written primarily for organizational and psychological scientists, the guide and recommendations are not limited to any particular scientific domain.

元分析评论是在组织和心理科学中产生累积知识的主要途径。在过去的一两年里，人们担心发表偏倚可能会影响荟萃分析结果，这可能会扭曲我们的累积知识并导致错误的实际建议。不幸的是，对于元分析师应该如何评估这种偏见，没有明确的指导方针。为了解决这个问题，本文开发了一份用户指南，其中包含用于评估元分析评论中的发表偏倚的最佳实践建议。为此，我们回顾了有关发表偏倚的文献，并制定了一个逐步的过程来评估发表偏倚的存在并衡量其对荟萃分析结果的影响。提供了工具和最佳实践的示例，以帮助元分析人员在他们自己的研究中实施该过程。尽管该论文主要是为组织和心理学科学家撰写的，但指南和建议并不限于任何特定的科学领域。