This editorial overview provides an introduction to the Suicide and Life‐Threatening Behaviors Special Issue: “Analytic and Methodological Innovations for Suicide‐Focused Research.” We outline several challenges faced by modern suicidologists, such as the need to integrate different analytical and methodological techniques from other fields with the unique data problems in suicide research. Therefore, the overall aim of this issue was to provide up‐to‐date methodological and analytical guidelines, recommendations, and considerations when conducting suicide‐focused research. The articles herein present this information in an accessible way for researchers/clinicians and do not require a comprehensive background in quantitative methods. We introduce the topics covered in this special issue, which include how to conduct power analyses using simulations, work with large data sets, use experimental therapeutics, and choose covariates, as well as open science considerations, decision‐making models, ordinal regression, machine learning, network analysis, and measurement considerations. Many of the topics covered in this issue provide step‐by‐step walkthroughs using worked examples with the accompanied code in free statistical programs (i.e., R). It is our hope that these articles provide suicidologists with valuable information and strategies that can help overcome some of the past limitations of suicide research, and improve the methodological rigor of our field.

中文翻译：

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编辑概述：以自杀为重点的研究的分析和方法创新

这篇社论概述介绍了自杀和威胁生命的行为特刊：“以自杀为重点的研究的分析和方法创新。” 我们概述了现代自杀学家面临的几个挑战，例如需要将其他领域的不同分析和方法技术与自杀研究中的独特数据问题相结合。因此，本期的总体目标是在进行以自杀为重点的研究时，提供最新的方法和分析指南、建议和注意事项。本文中的文章以研究人员/临床医生可以访问的方式提供这些信息，并且不需要定量方法的全面背景。我们介绍了本期特刊所涵盖的主题，包括如何使用模拟进行功效分析、处理大型数据集、使用实验疗法以及选择协变量，以及开放科学考虑、决策模型、序数回归、机器学习、网络分析和测量考虑。本期涵盖的许多主题提供了使用工作示例和免费统计程序（即 R）中随附代码的分步演练。我们希望这些文章能为自杀学家提供有价值的信息和策略，以帮助克服自杀研究过去的一些局限性，并提高我们领域的方法学严谨性。