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DPI: The Directed Prediction Index for Causal Direction Inference
from Observational Data
The Directed Prediction Index ('DPI') is a causal discovery method
for observational data designed to quantify the relative endogeneity
of outcome (Y) versus predictor (X) variables in regression models.
By comparing the coefficients of determination (R-squared)
between the Y-as-outcome and X-as-outcome models
while controlling for sufficient confounders and
simulating k random covariates, it can quantify relative endogeneity,
providing a necessary but insufficient condition for causal direction
from a less endogenous variable (X) to a more endogenous variable (Y).
Methodological details are provided at
<https://psychbruce.github.io/DPI/>.
This package also includes functions for data simulation and network
analysis (correlation, partial correlation, and Bayesian Networks).
| Version: |
2026.2 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
glue, crayon, cli, ggplot2, cowplot, qgraph, bnlearn, MASS |
| Suggests: |
bruceR, aplot, bayestestR |
| Published: |
2026-02-26 |
| DOI: |
10.32614/CRAN.package.DPI |
| Author: |
Han Wu Shuang Bao 
[aut, cre] |
| Maintainer: |
Han Wu Shuang Bao <baohws at foxmail.com> |
| BugReports: |
https://github.com/psychbruce/DPI/issues |
| License: |
GPL-3 |
| URL: |
https://psychbruce.github.io/DPI/ |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
DPI results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=DPI
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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