Percentiles are statistics pointing to the standing of a paper's citation impact relative to other papers in a given citation distribution. Percentile Ranks (PRs) often play an important role in evaluating the impact of scholars, institutions, and lines of study. Because PRs are so important for the assessment of scholarly impact, and because citation practices differ greatly across time and fields, various percentile approaches have been proposed to time- and field-normalize citations. Unfortunately, current popular methods often face significant problems in time- and field-normalization, including when papers are assigned to multiple fields or have been published by more than one unit (e.g., researchers or countries). They also face problems for estimating citation counts (CCs) for pre-defined PRs (e.g., the 90th PR). We offer a series of guidelines and procedures that, we argue, address these problems and others and provide a superior means to make the use of percentile methods more accurate and informative. In particular, we introduce two approaches, CP-IN and CP-EX, that should be preferred in bibliometric studies because they consider the complete citation distribution. Both approaches are based on cumulative frequencies in percentages (CPs). The paper further shows how bar graphs and beamplots can present PRs in a more meaningful and accurate manner.

中文翻译：

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对引文影响的百分位测量的评估，以及改进它们的建议

百分位数是指在给定的引文分布中，一篇论文相对于其他论文的引文影响地位的统计数据。百分位排名 (PR) 通常在评估学者、机构和研究方向的影响方面发挥重要作用。由于 PR 对于评估学术影响非常重要，并且由于引用实践在不同时间和领域有很大差异，因此已经提出了各种百分比方法来对引用进行时间和领域标准化。不幸的是，当前流行的方法在时间和领域归一化方面经常面临重大问题，包括当论文被分配到多个领域或由多个单位（例如，研究人员或国家）发表时。他们还面临着估计预定义 PR（例如，第 90 个 PR）的引用计数 (CC) 的问题。我们提供了一系列指南和程序，我们认为这些指南和程序可以解决这些问题和其他问题，并提供一种更好的方法来使百分位数方法的使用更准确和信息量更大。特别是，我们介绍了两种方法，CP-IN 和 CP-EX，它们在文献计量研究中应该是首选，因为它们考虑了完整的引文分布。这两种方法都基于百分比 (CP) 的累积频率。该论文进一步展示了条形图和波束图如何以更有意义和更准确的方式呈现 PR。这在文献计量研究中应该是首选，因为它们考虑了完整的引文分布。这两种方法都基于百分比 (CP) 的累积频率。该论文进一步展示了条形图和波束图如何以更有意义和更准确的方式呈现 PR。这在文献计量研究中应该是首选，因为它们考虑了完整的引文分布。这两种方法都基于百分比 (CP) 的累积频率。该论文进一步展示了条形图和波束图如何以更有意义和更准确的方式呈现 PR。