DPI: The Directed Prediction Index
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/>.
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