Software application profile: tpc and micd-R packages for causal discovery with incomplete cohort data.

IF 6.4 2区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH International journal of epidemiology Pub Date : 2024-08-14 DOI:10.1093/ije/dyae113

Ryan M Andrews, Christine W Bang, Vanessa Didelez, Janine Witte, Ronja Foraita

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引用次数: 0

Abstract

Motivation: The Peter Clark (PC) algorithm is a popular causal discovery method to learn causal graphs in a data-driven way. Until recently, existing PC algorithm implementations in R had important limitations regarding missing values, temporal structure or mixed measurement scales (categorical/continuous), which are all common features of cohort data. The new R packages presented here, micd and tpc, fill these gaps.

Implementation: micd and tpc packages are R packages.

General features: The micd package provides add-on functionality for dealing with missing values to the existing pcalg R package, including methods for multiple imputations relying on the Missing At Random assumption. Also, micd allows for mixed measurement scales assuming conditional Gaussianity. The tpc package efficiently exploits temporal information in a way that results in a more informative output that is less prone to statistical errors.

Availability: The tpc and micd packages are freely available on the Comprehensive R Archive Network (CRAN). Their source code is also available on GitHub (https://github.com/bips-hb/micd; https://github.com/bips-hb/tpc).

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软件应用简介：利用不完整队列数据发现因果关系的 tpc 和 micd-R 软件包。

动机彼得-克拉克（PC）算法是一种流行的因果发现方法，它以数据驱动的方式学习因果图。直到最近，R语言中现有的PC算法在缺失值、时间结构或混合测量尺度（分类/连续）方面都有很大的局限性，而这些都是队列数据的常见特征。本文介绍的新 R 软件包 micd 和 tpc 填补了这些空白。实现：micd 和 tpc 软件包均为 R 软件包：一般特点：micd 软件包为现有的 pcalg R 软件包提供了处理缺失值的附加功能，包括根据随机缺失假设进行多重估算的方法。此外，micd 还允许假设条件高斯性的混合测量尺度。tpc 软件包有效地利用了时间信息，使输出结果信息量更大，不易出现统计错误：tpc和micd软件包可在R档案综合网络（CRAN）上免费获取。它们的源代码也可在 GitHub 上获取（https://github.com/bips-hb/micd; https://github.com/bips-hb/tpc）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International journal of epidemiology 医学-公共卫生、环境卫生与职业卫生

CiteScore

13.60

自引率

2.60%

发文量

226

审稿时长

3 months

期刊介绍： The International Journal of Epidemiology is a vital resource for individuals seeking to stay updated on the latest advancements and emerging trends in the field of epidemiology worldwide. The journal fosters communication among researchers, educators, and practitioners involved in the study, teaching, and application of epidemiology pertaining to both communicable and non-communicable diseases. It also includes research on health services and medical care. Furthermore, the journal presents new methodologies in epidemiology and statistics, catering to professionals working in social and preventive medicine. Published six times a year, the International Journal of Epidemiology provides a comprehensive platform for the analysis of data. Overall, this journal is an indispensable tool for staying informed and connected within the dynamic realm of epidemiology.