# ipd: an R package for conducting inference on predicted data

## TL;DR

The ipd R package helps users perform statistical inference on data where outcomes are partially predicted by AI or machine learning models.

## Contribution

ipd introduces a unified R package implementing recent methods for inference on predicted data with a simple interface.

## Key findings

- The package supports multiple methods for inference on predicted data in a single function.
- It includes tools for model inspection like print, summary, and augment methods.
- The package is available on CRAN and GitHub with full documentation.

## Abstract

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.