DPI-package: DPI: The Directed Prediction Index

In DPI: The Directed Prediction Index

DPI: The Directed Prediction Index

Description

The Directed Prediction Index ('DPI') is a simulation-based 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/.

Author(s)

Maintainer: Han Wu Shuang Bao [e-mail] (ORCID)

See Also

Useful links:

• https://psychbruce.github.io/DPI/

• Report bugs at https://github.com/psychbruce/DPI/issues

DPI documentation built on Aug. 21, 2025, 5:42 p.m.