Salerno Stephen, Miao Jiacheng, Afiaz Awan, Hoffman Kentaro, Neufeld Anna, Lu Qiongshi, McCormick Tyler H, Leek Jeffrey T
Public Health Sciences, Biostatistics, Fred Hutchinson Cancer Center, Seattle, WA 98109, United States.
Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53726, United States.
Bioinformatics. 2025 Feb 4;41(2). doi: 10.1093/bioinformatics/btaf055.
ipd is an open-source R software package for the downstream modeling of an outcome and its associated features where a potentially sizable portion of the outcome data has been imputed by an artificial intelligence or machine learning prediction algorithm. The package implements several recent proposed methods for inference on predicted data with a single, user-friendly wrapper function, ipd. The package also provides custom print, summary, tidy, glance, and augment methods to facilitate easy model inspection. This document introduces the ipd software package and provides a demonstration of its basic usage.
ipd is freely available on CRAN or as a developer version at our GitHub page: github.com/ipd-tools/ipd. Full documentation, including detailed instructions and a usage 'vignette' are available at github.com/ipd-tools/ipd.
ipd是一个开源的R软件包，用于对结果及其相关特征进行下游建模，其中结果数据的潜在相当大一部分已由人工智能或机器学习预测算法估算。该软件包通过一个用户友好的包装函数ipd实现了几种最近提出的对预测数据进行推断的方法。该软件包还提供了自定义的打印、汇总、整理、浏览和增强方法，以方便模型检查。本文档介绍了ipd软件包并演示了其基本用法。
ipd可在CRAN上免费获取，也可在我们的GitHub页面github.com/ipd-tools/ipd上作为开发版本获取。完整的文档，包括详细说明和使用“vignette”，可在github.com/ipd-tools/ipd上获取。
