DPI: The Directed Prediction Index

The Directed Prediction Index ('DPI') is a simulation-based and conservative method for quantifying the relative endogeneity (relative dependence) of outcome (Y) versus predictor (X) variables in multiple linear regression models. By comparing the proportion of variance explained (R-squared) between the Y-as-outcome model and the X-as-outcome model while controlling for a sufficient number of potential confounding variables, it suggests a more plausible influence direction from a more exogenous variable (X) to a more endogenous variable (Y). Methodological details are provided at <https://psychbruce.github.io/DPI/>.

Getting started

Package details

AuthorHan-Wu-Shuang Bao [aut, cre] (ORCID: <https://orcid.org/0000-0003-3043-710X>)
MaintainerHan-Wu-Shuang Bao <baohws@foxmail.com>
LicenseGPL-3
Version2025.6
URL https://psychbruce.github.io/DPI/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("DPI")

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DPI documentation built on June 18, 2025, 9:08 a.m.