The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of Psychological Methods. Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of applications that are possible with modern missing data techniques has increased dramatically, and software options are light years ahead of where they were. This article provides an update on the state of the art that catalogs important innovations from the past two decades of missing data research. The paper addresses topics described in the original paper, including developments related to missing data theory, full information maximum likelihood, Bayesian estimation, multiple imputation, and models for missing not at random processes. The paper also describes newer factored regression specifications and missing data handling for multilevel models, both of which have been a focus of recent research. The paper concludes with a summary of the current software landscape and a discussion of several practical issues. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译：

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缺失数据：最新技术的更新。

2022 年是 Joseph Schafer 和 John Graham 题为“缺失数据：我们对最新技术的看法”的论文发表 20 周年，该论文目前是心理学方法史上被引用次数最多的论文。自 2002 年以来发生了很大变化，因为缺失数据方法不断发展和改进；现代缺失数据技术的应用范围已大大增加，软件选项也比以前多了光年。本文提供了对过去二十年缺失数据研究的重要创新进行分类的最新技术水平。本文讨论了原始论文中描述的主题，包括与缺失数据理论、全信息最大似然、贝叶斯估计、多重插补、和不随机过程缺失的模型。该论文还描述了更新的因子回归规范和多级模型的缺失数据处理，这两者都是近期研究的重点。本文最后总结了当前的软件前景，并讨论了几个实际问题。（PsycInfo 数据库记录 (c) 2023 APA，保留所有权利）。