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).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2026.2 |
rolling linux/jammy R-4.5 | DPI_2026.2.tar.gz |
132.7 KiB |
2026.2 |
rolling linux/noble R-4.5 | DPI_2026.2.tar.gz |
132.6 KiB |
2026.2 |
rolling source/ R- | DPI_2026.2.tar.gz |
32.5 KiB |
2026.2 |
latest linux/jammy R-4.5 | DPI_2026.2.tar.gz |
132.7 KiB |
2026.2 |
latest linux/noble R-4.5 | DPI_2026.2.tar.gz |
132.6 KiB |
2026.2 |
latest source/ R- | DPI_2026.2.tar.gz |
32.5 KiB |
2026.2 |
2026-04-26 source/ R- | DPI_2026.2.tar.gz |
32.5 KiB |
2026.2 |
2026-04-23 source/ R- | DPI_2026.2.tar.gz |
32.5 KiB |
2026.2 |
2026-04-09 windows/windows R-4.5 | DPI_2026.2.zip |
135.0 KiB |